jaroslav-kuchar/ESF-CZ-2007-2013.ipynb Secret

## ESF-CZ-2007-2013.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Outlier detection experiment: ESF-CZ-2007-2013"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Author: __Jaroslav Kuchař__ *(firstname.lastname@{vse.cz,fit.cvut.cz})*\n",
    "  * Department of Information and Knowledge Engineering, Faculty of Informatics and Statistics, University of Economics Prague \n",
    "  * Web Intelligence Research Group, Faculty of Information Technology, Czech Technical University in Prague\n",
    "                "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Table of contents:\n",
    "1. [Ad-hoc preprocessing of data](#Preprocessing)\n",
    "1. [Summary](#Summary)\n",
    "1. [Outlier detection](#Outlier-detection) with algorithm based on frequent itemsets mining.\n",
    "  * package [fpmoutliers](https://github.com/jaroslav-kuchar/fpmoutliers)\n",
    "1. Preliminary [visualizations](#Visualizations) and [explanations](#Explanations) of resuls."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "options(warn=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# load data from local file\n",
    "localPath = \"./esf_cz_2007_2013_projects.csv.gz\"\n",
    "data <- read.csv(gzfile(localPath))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# remove URI prefixes\n",
    "library(plyr)\n",
    "for(col in colnames(data)){\n",
    "    if(!is.numeric(data[[col]])){\n",
    "        aa<-sapply(levels(data[[col]]), function(x) {\n",
    "            if(grepl(\"/\",x)==TRUE){\n",
    "                as.character(URLdecode(substr(x, regexpr(\"\\\\/[^\\\\/]*$\",x)[1]+1, nchar(x))))\n",
    "            } else {\n",
    "                x\n",
    "            }\n",
    "        })\n",
    "        data[[col]] <- mapvalues(data[[col]], from=levels(data[[col]]), to=aa)\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>107311</li>\n",
       "\t<li>14</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 107311\n",
       "\\item 14\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 107311\n",
       "2. 14\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 107311     14"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'project'</li>\n",
       "\t<li>'partner'</li>\n",
       "\t<li>'partnerTypeBroader'</li>\n",
       "\t<li>'numberOfEmployeesMin'</li>\n",
       "\t<li>'numberOfEmployeesMax'</li>\n",
       "\t<li>'operationalProgramme'</li>\n",
       "\t<li>'operationalProgrammeBroader'</li>\n",
       "\t<li>'date'</li>\n",
       "\t<li>'allocatedCz'</li>\n",
       "\t<li>'allocatedEu'</li>\n",
       "\t<li>'paidCz'</li>\n",
       "\t<li>'paidEu'</li>\n",
       "\t<li>'certifiedCz'</li>\n",
       "\t<li>'certifiedEu'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'project'\n",
       "\\item 'partner'\n",
       "\\item 'partnerTypeBroader'\n",
       "\\item 'numberOfEmployeesMin'\n",
       "\\item 'numberOfEmployeesMax'\n",
       "\\item 'operationalProgramme'\n",
       "\\item 'operationalProgrammeBroader'\n",
       "\\item 'date'\n",
       "\\item 'allocatedCz'\n",
       "\\item 'allocatedEu'\n",
       "\\item 'paidCz'\n",
       "\\item 'paidEu'\n",
       "\\item 'certifiedCz'\n",
       "\\item 'certifiedEu'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'project'\n",
       "2. 'partner'\n",
       "3. 'partnerTypeBroader'\n",
       "4. 'numberOfEmployeesMin'\n",
       "5. 'numberOfEmployeesMax'\n",
       "6. 'operationalProgramme'\n",
       "7. 'operationalProgrammeBroader'\n",
       "8. 'date'\n",
       "9. 'allocatedCz'\n",
       "10. 'allocatedEu'\n",
       "11. 'paidCz'\n",
       "12. 'paidEu'\n",
       "13. 'certifiedCz'\n",
       "14. 'certifiedEu'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"project\"                     \"partner\"                    \n",
       " [3] \"partnerTypeBroader\"          \"numberOfEmployeesMin\"       \n",
       " [5] \"numberOfEmployeesMax\"        \"operationalProgramme\"       \n",
       " [7] \"operationalProgrammeBroader\" \"date\"                       \n",
       " [9] \"allocatedCz\"                 \"allocatedEu\"                \n",
       "[11] \"paidCz\"                      \"paidEu\"                     \n",
       "[13] \"certifiedCz\"                 \"certifiedEu\"                "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>project</th><th scope=col>partner</th><th scope=col>partnerTypeBroader</th><th scope=col>numberOfEmployeesMin</th><th scope=col>numberOfEmployeesMax</th><th scope=col>operationalProgramme</th><th scope=col>operationalProgrammeBroader</th><th scope=col>date</th><th scope=col>allocatedCz</th><th scope=col>allocatedEu</th><th scope=col>paidCz</th><th scope=col>paidEu</th><th scope=col>certifiedCz</th><th scope=col>certifiedEu</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>CZ-1-01-1-1-00-06-0019            </td><td>CZ70994234                        </td><td>Stát a jeho instituce a organizace</td><td>NA                                </td><td>NA                                </td><td>1-1-1                             </td><td>1-1                               </td><td>2008-07-02                        </td><td>3706235000                        </td><td>2600257413                        </td><td>3715323036                        </td><td>2606427442                        </td><td>3658862576                        </td><td>2566814783                        </td></tr>\n",
       "\t<tr><td>CZ-1-01-1-1-00-06-0019            </td><td>CZ70994234                        </td><td>Stát a jeho instituce a organizace</td><td>NA                                </td><td>NA                                </td><td>1-1-1                             </td><td>1-1                               </td><td>2008-07-02                        </td><td>3706235000                        </td><td>2600257413                        </td><td>3715323036                        </td><td>2606427442                        </td><td>3658862576                        </td><td>2566814783                        </td></tr>\n",
       "\t<tr><td>CZ-1-01-1-1-00-07-0006            </td><td>CZ70994234                        </td><td>Stát a jeho instituce a organizace</td><td>NA                                </td><td>NA                                </td><td>1-1-1                             </td><td>1-1                               </td><td>2008-07-02                        </td><td>1181842444                        </td><td> 841525002                        </td><td>1181842444                        </td><td> 873972487                        </td><td>1181842444                        </td><td> 873972487                        </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllll}\n",
       " project & partner & partnerTypeBroader & numberOfEmployeesMin & numberOfEmployeesMax & operationalProgramme & operationalProgrammeBroader & date & allocatedCz & allocatedEu & paidCz & paidEu & certifiedCz & certifiedEu\\\\\n",
       "\\hline\n",
       "\t CZ-1-01-1-1-00-06-0019             & CZ70994234                         & Stát a jeho instituce a organizace & NA                                 & NA                                 & 1-1-1                              & 1-1                                & 2008-07-02                         & 3706235000                         & 2600257413                         & 3715323036                         & 2606427442                         & 3658862576                         & 2566814783                        \\\\\n",
       "\t CZ-1-01-1-1-00-06-0019             & CZ70994234                         & Stát a jeho instituce a organizace & NA                                 & NA                                 & 1-1-1                              & 1-1                                & 2008-07-02                         & 3706235000                         & 2600257413                         & 3715323036                         & 2606427442                         & 3658862576                         & 2566814783                        \\\\\n",
       "\t CZ-1-01-1-1-00-07-0006             & CZ70994234                         & Stát a jeho instituce a organizace & NA                                 & NA                                 & 1-1-1                              & 1-1                                & 2008-07-02                         & 1181842444                         &  841525002                         & 1181842444                         &  873972487                         & 1181842444                         &  873972487                        \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "project | partner | partnerTypeBroader | numberOfEmployeesMin | numberOfEmployeesMax | operationalProgramme | operationalProgrammeBroader | date | allocatedCz | allocatedEu | paidCz | paidEu | certifiedCz | certifiedEu | \n",
       "|---|---|---|\n",
       "| CZ-1-01-1-1-00-06-0019             | CZ70994234                         | Stát a jeho instituce a organizace | NA                                 | NA                                 | 1-1-1                              | 1-1                                | 2008-07-02                         | 3706235000                         | 2600257413                         | 3715323036                         | 2606427442                         | 3658862576                         | 2566814783                         | \n",
       "| CZ-1-01-1-1-00-06-0019             | CZ70994234                         | Stát a jeho instituce a organizace | NA                                 | NA                                 | 1-1-1                              | 1-1                                | 2008-07-02                         | 3706235000                         | 2600257413                         | 3715323036                         | 2606427442                         | 3658862576                         | 2566814783                         | \n",
       "| CZ-1-01-1-1-00-07-0006             | CZ70994234                         | Stát a jeho instituce a organizace | NA                                 | NA                                 | 1-1-1                              | 1-1                                | 2008-07-02                         | 1181842444                         |  841525002                         | 1181842444                         |  873972487                         | 1181842444                         |  873972487                         | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  project                partner    partnerTypeBroader                \n",
       "1 CZ-1-01-1-1-00-06-0019 CZ70994234 Stát a jeho instituce a organizace\n",
       "2 CZ-1-01-1-1-00-06-0019 CZ70994234 Stát a jeho instituce a organizace\n",
       "3 CZ-1-01-1-1-00-07-0006 CZ70994234 Stát a jeho instituce a organizace\n",
       "  numberOfEmployeesMin numberOfEmployeesMax operationalProgramme\n",
       "1 NA                   NA                   1-1-1               \n",
       "2 NA                   NA                   1-1-1               \n",
       "3 NA                   NA                   1-1-1               \n",
       "  operationalProgrammeBroader date       allocatedCz allocatedEu paidCz    \n",
       "1 1-1                         2008-07-02 3706235000  2600257413  3715323036\n",
       "2 1-1                         2008-07-02 3706235000  2600257413  3715323036\n",
       "3 1-1                         2008-07-02 1181842444   841525002  1181842444\n",
       "  paidEu     certifiedCz certifiedEu\n",
       "1 2606427442 3658862576  2566814783 \n",
       "2 2606427442 3658862576  2566814783 \n",
       "3  873972487 1181842444   873972487 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "                    project             partner      \n",
       " CZ-1-07-1-1-00-56-0296 :     6   CZ00020729:   558  \n",
       " CZ-1-07-1-1-00-57-1509 :     6   CZ61989592:   542  \n",
       " CZ-1-07-1-4-00-21-2068 :     6   CZ70994234:   514  \n",
       " CZ-1-02-1-1-00-09-06052:     4   CZ72496991:   442  \n",
       " CZ-1-02-1-3-00-10-09192:     4   CZ44992785:   432  \n",
       " CZ-1-02-1-3-00-14-23438:     4   CZ00164801:   426  \n",
       " (Other)                :107281   (Other)   :104397  \n",
       "                           partnerTypeBroader numberOfEmployeesMin\n",
       " Obce                               :45963    Min.   :   0.0      \n",
       " Podnikatelské subjekty             :23095    1st Qu.:  10.0      \n",
       " Ostatní                            :23009    Median :  25.0      \n",
       " Komory, profesní a zájmové sdružení: 4196    Mean   : 253.2      \n",
       " Stát a jeho instituce a organizace : 4118    3rd Qu.: 100.0      \n",
       " Vzdělávací a výzkumné instituce    : 3006    Max.   :5000.0      \n",
       " (Other)                            : 3924    NA's   :9206        \n",
       " numberOfEmployeesMax operationalProgramme operationalProgrammeBroader\n",
       " Min.   :   0.0       2-3-2  :10691        7-1    :19122              \n",
       " 1st Qu.:  19.0       6-2-1  : 9237        2-3    :11570              \n",
       " Median :  49.0       7-1-1  : 8944        6-2    : 9237              \n",
       " Mean   : 416.3       2-4-1  : 5999        2-6    : 6850              \n",
       " 3rd Qu.: 199.0       3-2-2  : 5738        2-4    : 6251              \n",
       " Max.   :9999.0       7-1-4  : 5667        3-2    : 5738              \n",
       " NA's   :9206         (Other):61035        (Other):48543              \n",
       "         date         allocatedCz         allocatedEu       \n",
       " 2015-07-20:  2391   Min.   :7.000e+02   Min.   :5.950e+02  \n",
       " 2015-09-22:  1873   1st Qu.:8.478e+05   1st Qu.:7.121e+05  \n",
       " 2015-09-29:  1292   Median :2.381e+06   Median :2.031e+06  \n",
       " 2009-07-15:   574   Mean   :1.418e+07   Mean   :1.149e+07  \n",
       " 2009-07-14:   567   3rd Qu.:6.123e+06   3rd Qu.:5.233e+06  \n",
       " 2009-07-09:   555   Max.   :2.003e+10   Max.   :1.020e+10  \n",
       " (Other)   :100059                                          \n",
       "     paidCz              paidEu           certifiedCz       \n",
       " Min.   :0.000e+00   Min.   :0.000e+00   Min.   :0.000e+00  \n",
       " 1st Qu.:8.024e+05   1st Qu.:6.736e+05   1st Qu.:0.000e+00  \n",
       " Median :2.233e+06   Median :1.900e+06   Median :1.059e+06  \n",
       " Mean   :1.295e+07   Mean   :1.058e+07   Mean   :1.033e+07  \n",
       " 3rd Qu.:5.642e+06   3rd Qu.:4.821e+06   3rd Qu.:4.301e+06  \n",
       " Max.   :1.193e+10   Max.   :9.022e+09   Max.   :9.753e+09  \n",
       "                                                            \n",
       "  certifiedEu       \n",
       " Min.   :0.000e+00  \n",
       " 1st Qu.:0.000e+00  \n",
       " Median :8.919e+05  \n",
       " Mean   :8.458e+06  \n",
       " 3rd Qu.:3.682e+06  \n",
       " Max.   :7.449e+09  \n",
       "                    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# overview of data\n",
    "dim(data)\n",
    "colnames(data)\n",
    "head(data,3)\n",
    "summary(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Outlier detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: Matrix\n",
      "\n",
      "Attaching package: ‘arules’\n",
      "\n",
      "The following objects are masked from ‘package:base’:\n",
      "\n",
      "    abbreviate, write\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# load libraries/dependencies\n",
    "library(fpmoutliers)\n",
    "library(arules)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>partnerTypeBroader</th><th scope=col>operationalProgrammeBroader</th><th scope=col>amount</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>Stát a jeho instituce a organizace</td><td>1-1                               </td><td>[2.56e+09,2.57e+09)               </td></tr>\n",
       "\t<tr><td>Stát a jeho instituce a organizace</td><td>1-1                               </td><td>[2.56e+09,2.57e+09)               </td></tr>\n",
       "\t<tr><td>Stát a jeho instituce a organizace</td><td>1-1                               </td><td>[8.72e+08,8.79e+08)               </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       " partnerTypeBroader & operationalProgrammeBroader & amount\\\\\n",
       "\\hline\n",
       "\t Stát a jeho instituce a organizace & 1-1                                & {[}2.56e+09,2.57e+09)             \\\\\n",
       "\t Stát a jeho instituce a organizace & 1-1                                & {[}2.56e+09,2.57e+09)             \\\\\n",
       "\t Stát a jeho instituce a organizace & 1-1                                & {[}8.72e+08,8.79e+08)             \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "partnerTypeBroader | operationalProgrammeBroader | amount | \n",
       "|---|---|---|\n",
       "| Stát a jeho instituce a organizace | 1-1                                | [2.56e+09,2.57e+09)                | \n",
       "| Stát a jeho instituce a organizace | 1-1                                | [2.56e+09,2.57e+09)                | \n",
       "| Stát a jeho instituce a organizace | 1-1                                | [8.72e+08,8.79e+08)                | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  partnerTypeBroader                 operationalProgrammeBroader\n",
       "1 Stát a jeho instituce a organizace 1-1                        \n",
       "2 Stát a jeho instituce a organizace 1-1                        \n",
       "3 Stát a jeho instituce a organizace 1-1                        \n",
       "  amount             \n",
       "1 [2.56e+09,2.57e+09)\n",
       "2 [2.56e+09,2.57e+09)\n",
       "3 [8.72e+08,8.79e+08)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# select a subset of columns\n",
    "dataOutliers <- data[c(\"partnerTypeBroader\", \"operationalProgrammeBroader\", \"certifiedEu\")]\n",
    "colnames(dataOutliers)[colnames(dataOutliers) == 'certifiedEu'] <- 'amount'\n",
    "# discretize amount using clustering/intervals\n",
    "# dataOutliers$amount <- discretize(as.numeric(dataOutliers$amount), method = \"cluster\", categories = 1000)\n",
    "# dataOutliers$amount <- discretize(as.numeric(dataOutliers$amount), method = \"frequency\", categories = 1000)\n",
    "dataOutliers$amount <- discretize(as.numeric(dataOutliers$amount), method = \"interval\", categories = 1000)\n",
    "head(dataOutliers, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Apriori\n",
      "\n",
      "Parameter specification:\n",
      " confidence minval smax arem  aval originalSupport maxtime support minlen\n",
      "         NA    0.1    1 none FALSE            TRUE       5   1e-04      1\n",
      " maxlen            target   ext\n",
      "      3 frequent itemsets FALSE\n",
      "\n",
      "Algorithmic control:\n",
      " filter tree heap memopt load sort verbose\n",
      "    0.1 TRUE TRUE  FALSE TRUE    2    TRUE\n",
      "\n",
      "Absolute minimum support count: 10 \n",
      "\n",
      "set item appearances ...[0 item(s)] done [0.00s].\n",
      "set transactions ...[242 item(s), 107311 transaction(s)] done [0.03s].\n",
      "sorting and recoding items ... [136 item(s)] done [0.00s].\n",
      "creating transaction tree ... done [0.05s].\n",
      "checking subsets of size 1 2 3 done [0.00s].\n",
      "writing ... [1245 set(s)] done [0.00s].\n",
      "creating S4 object  ... done [0.02s].\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "FI lengths: 0.000106096267700195\n",
      "FI qualities: 0.00132107734680176\n",
      "FI coverages: 20.6454348564148\n",
      "FI multiply: 0.0487737655639648\n",
      "Penalization: 0.0540149211883545\n",
      "Means: 19.0463018417358\n"
     ]
    }
   ],
   "source": [
    "# delete the \"scores\" column if available\n",
    "if(\"scores\" %in% colnames(dataOutliers)){\n",
    "    dataOutliers[\"scores\"] <- NULL\n",
    "}\n",
    "# outlier detection algorithm\n",
    "model <- FPI(dataOutliers, minSupport = 0.0001, mlen = 0)\n",
    "dataOutliers$scores <- model$scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "### Top-10 outliers"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>partnerTypeBroader</th><th scope=col>operationalProgrammeBroader</th><th scope=col>amount</th><th scope=col>scores</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>54000</th><td>Vzdělávací a výzkumné instituce</td><td>5-1                            </td><td>[3.34e+09,3.34e+09)            </td><td>71552.57                       </td></tr>\n",
       "\t<tr><th scope=row>54001</th><td>Vzdělávací a výzkumné instituce</td><td>5-1                            </td><td>[3.34e+09,3.34e+09)            </td><td>71552.57                       </td></tr>\n",
       "\t<tr><th scope=row>54002</th><td>Vzdělávací a výzkumné instituce</td><td>5-1                            </td><td>[5.96e+08,6.03e+08)            </td><td>71552.57                       </td></tr>\n",
       "\t<tr><th scope=row>54003</th><td>Vzdělávací a výzkumné instituce</td><td>5-1                            </td><td>[5.96e+08,6.03e+08)            </td><td>71552.57                       </td></tr>\n",
       "\t<tr><th scope=row>54004</th><td>Vzdělávací a výzkumné instituce</td><td>5-1                            </td><td>[1.18e+09,1.18e+09)            </td><td>71552.57                       </td></tr>\n",
       "\t<tr><th scope=row>54005</th><td>Vzdělávací a výzkumné instituce</td><td>5-1                            </td><td>[1.18e+09,1.18e+09)            </td><td>71552.57                       </td></tr>\n",
       "\t<tr><th scope=row>46702</th><td>Ostatní                        </td><td>11-4                           </td><td>[3.05e+08,3.13e+08)            </td><td>71542.22                       </td></tr>\n",
       "\t<tr><th scope=row>53997</th><td>Ostatní                        </td><td>5-1                            </td><td>[1.23e+09,1.24e+09)            </td><td>71542.22                       </td></tr>\n",
       "\t<tr><th scope=row>53998</th><td>Ostatní                        </td><td>5-1                            </td><td>[1.23e+09,1.24e+09)            </td><td>71542.22                       </td></tr>\n",
       "\t<tr><th scope=row>53999</th><td>Ostatní                        </td><td>5-1                            </td><td>[1.23e+09,1.24e+09)            </td><td>71542.22                       </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       "  & partnerTypeBroader & operationalProgrammeBroader & amount & scores\\\\\n",
       "\\hline\n",
       "\t54000 & Vzdělávací a výzkumné instituce & 5-1                             & {[}3.34e+09,3.34e+09)           & 71552.57                       \\\\\n",
       "\t54001 & Vzdělávací a výzkumné instituce & 5-1                             & {[}3.34e+09,3.34e+09)           & 71552.57                       \\\\\n",
       "\t54002 & Vzdělávací a výzkumné instituce & 5-1                             & {[}5.96e+08,6.03e+08)           & 71552.57                       \\\\\n",
       "\t54003 & Vzdělávací a výzkumné instituce & 5-1                             & {[}5.96e+08,6.03e+08)           & 71552.57                       \\\\\n",
       "\t54004 & Vzdělávací a výzkumné instituce & 5-1                             & {[}1.18e+09,1.18e+09)           & 71552.57                       \\\\\n",
       "\t54005 & Vzdělávací a výzkumné instituce & 5-1                             & {[}1.18e+09,1.18e+09)           & 71552.57                       \\\\\n",
       "\t46702 & Ostatní                         & 11-4                            & {[}3.05e+08,3.13e+08)           & 71542.22                       \\\\\n",
       "\t53997 & Ostatní                         & 5-1                             & {[}1.23e+09,1.24e+09)           & 71542.22                       \\\\\n",
       "\t53998 & Ostatní                         & 5-1                             & {[}1.23e+09,1.24e+09)           & 71542.22                       \\\\\n",
       "\t53999 & Ostatní                         & 5-1                             & {[}1.23e+09,1.24e+09)           & 71542.22                       \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | partnerTypeBroader | operationalProgrammeBroader | amount | scores | \n",
       "|---|---|---|---|---|---|---|---|---|---|\n",
       "| 54000 | Vzdělávací a výzkumné instituce | 5-1                             | [3.34e+09,3.34e+09)             | 71552.57                        | \n",
       "| 54001 | Vzdělávací a výzkumné instituce | 5-1                             | [3.34e+09,3.34e+09)             | 71552.57                        | \n",
       "| 54002 | Vzdělávací a výzkumné instituce | 5-1                             | [5.96e+08,6.03e+08)             | 71552.57                        | \n",
       "| 54003 | Vzdělávací a výzkumné instituce | 5-1                             | [5.96e+08,6.03e+08)             | 71552.57                        | \n",
       "| 54004 | Vzdělávací a výzkumné instituce | 5-1                             | [1.18e+09,1.18e+09)             | 71552.57                        | \n",
       "| 54005 | Vzdělávací a výzkumné instituce | 5-1                             | [1.18e+09,1.18e+09)             | 71552.57                        | \n",
       "| 46702 | Ostatní                         | 11-4                            | [3.05e+08,3.13e+08)             | 71542.22                        | \n",
       "| 53997 | Ostatní                         | 5-1                             | [1.23e+09,1.24e+09)             | 71542.22                        | \n",
       "| 53998 | Ostatní                         | 5-1                             | [1.23e+09,1.24e+09)             | 71542.22                        | \n",
       "| 53999 | Ostatní                         | 5-1                             | [1.23e+09,1.24e+09)             | 71542.22                        | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "      partnerTypeBroader              operationalProgrammeBroader\n",
       "54000 Vzdělávací a výzkumné instituce 5-1                        \n",
       "54001 Vzdělávací a výzkumné instituce 5-1                        \n",
       "54002 Vzdělávací a výzkumné instituce 5-1                        \n",
       "54003 Vzdělávací a výzkumné instituce 5-1                        \n",
       "54004 Vzdělávací a výzkumné instituce 5-1                        \n",
       "54005 Vzdělávací a výzkumné instituce 5-1                        \n",
       "46702 Ostatní                         11-4                       \n",
       "53997 Ostatní                         5-1                        \n",
       "53998 Ostatní                         5-1                        \n",
       "53999 Ostatní                         5-1                        \n",
       "      amount              scores  \n",
       "54000 [3.34e+09,3.34e+09) 71552.57\n",
       "54001 [3.34e+09,3.34e+09) 71552.57\n",
       "54002 [5.96e+08,6.03e+08) 71552.57\n",
       "54003 [5.96e+08,6.03e+08) 71552.57\n",
       "54004 [1.18e+09,1.18e+09) 71552.57\n",
       "54005 [1.18e+09,1.18e+09) 71552.57\n",
       "46702 [3.05e+08,3.13e+08) 71542.22\n",
       "53997 [1.23e+09,1.24e+09) 71542.22\n",
       "53998 [1.23e+09,1.24e+09) 71542.22\n",
       "53999 [1.23e+09,1.24e+09) 71542.22"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "### 3 instances with lowest outlier score"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>partnerTypeBroader</th><th scope=col>operationalProgrammeBroader</th><th scope=col>amount</th><th scope=col>scores</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>96917</th><td>Ostatní            </td><td>7-1                </td><td>[0.00e+00,7.45e+06)</td><td>3.204272           </td></tr>\n",
       "\t<tr><th scope=row>96918</th><td>Ostatní            </td><td>7-1                </td><td>[0.00e+00,7.45e+06)</td><td>3.204272           </td></tr>\n",
       "\t<tr><th scope=row>96919</th><td>Ostatní            </td><td>7-1                </td><td>[0.00e+00,7.45e+06)</td><td>3.204272           </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       "  & partnerTypeBroader & operationalProgrammeBroader & amount & scores\\\\\n",
       "\\hline\n",
       "\t96917 & Ostatní               & 7-1                   & {[}0.00e+00,7.45e+06) & 3.204272             \\\\\n",
       "\t96918 & Ostatní               & 7-1                   & {[}0.00e+00,7.45e+06) & 3.204272             \\\\\n",
       "\t96919 & Ostatní               & 7-1                   & {[}0.00e+00,7.45e+06) & 3.204272             \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | partnerTypeBroader | operationalProgrammeBroader | amount | scores | \n",
       "|---|---|---|\n",
       "| 96917 | Ostatní             | 7-1                 | [0.00e+00,7.45e+06) | 3.204272            | \n",
       "| 96918 | Ostatní             | 7-1                 | [0.00e+00,7.45e+06) | 3.204272            | \n",
       "| 96919 | Ostatní             | 7-1                 | [0.00e+00,7.45e+06) | 3.204272            | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "      partnerTypeBroader operationalProgrammeBroader amount             \n",
       "96917 Ostatní            7-1                         [0.00e+00,7.45e+06)\n",
       "96918 Ostatní            7-1                         [0.00e+00,7.45e+06)\n",
       "96919 Ostatní            7-1                         [0.00e+00,7.45e+06)\n",
       "      scores  \n",
       "96917 3.204272\n",
       "96918 3.204272\n",
       "96919 3.204272"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQ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\n9VvZttfk/Dl7VNpJ8jn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EX6UulByRfJ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\nRwj8f06rnCXO/g92AAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “Histogram of dataOutliers$scores”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# list outliers\n",
    "dataOutliers <- dataOutliers[order(dataOutliers$scores, decreasing = TRUE),]\n",
    "# rownames(dataOutliers) <- NULL\n",
    "IRdisplay::display_markdown(\"### Top-10 outliers\")\n",
    "head(dataOutliers, 10)\n",
    "IRdisplay::display_markdown(\"### 3 instances with lowest outlier score\")\n",
    "tail(dataOutliers, 3)\n",
    "# Histogram of scores\n",
    "options(repr.plot.width=5)\n",
    "options(repr.plot.height = 3)\n",
    "hist(dataOutliers$scores)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# generate barplots\n",
    "visualyEplain <- function(data, anomalyIndex) {\n",
    "    anomaly <- data[anomalyIndex,]\n",
    "    cols <- colnames(data)\n",
    "    cols <- setdiff(cols, c(\"scores\"))\n",
    "    par(mfrow=c(ceiling(length(cols)/2),2), mar=c(2,2,1,1))\n",
    "    for(col in cols){\n",
    "      colors <- rep(\"gray\",length(unique(data[[col]])))\n",
    "      colors[which(names(sort(table(data[[col]])))==anomaly[[col]])] <- \"red\"\n",
    "      barplot(sort(table(data[[col]])), col=colors, main = paste(col,\"=\",anomaly[[col]], \"(\",(sort(table(data[[col]])))[which(names(sort(table(data[[col]])))==anomaly[[col]])],\")\", sep=\"\"))\n",
    "    }\n",
    "  }"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Outlier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RbTvP32NRMsPT+E8SfkZ4VZbWjLOY37WGrO9vHDvJ01Zzu/rfXEc03eufxLOu5E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bKd5eo4v30f9J6ddk39vllbfU4PWM/Ifq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\nx5M/NRXe4D+j8T5Ju3KDu6Nl4uW9Hnc4lCr+5FPcgVSvDqweW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AAB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\n8C5R4H+Z0XVOi6h5SwAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “amount=[3.34e+09,3.34e+09)(2)”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.width=10)\n",
    "options(repr.plot.height = 5)\n",
    "visualyEplain(dataOutliers, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3K08rf1YOUq5VZiqhVJrmd5rQ6yuVXcKCou796v9eNBx6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",
      "text/plain": [
       "Plot with title “amount=[3.34e+09,3.34e+09)”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "do <- dataOutliers\n",
    "do$scores <- NULL\n",
    "visualizeInstance(do, 1)\n",
    "# dev.copy(pdf,'exp-outlier.pdf', width = 10, height = 7)\n",
    "# dev.off()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inlier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAAQgAAEIVCUBHFhVeVjo\nFAQgAAEIQAACEIAABCAAAQhAAAIQgEAggAMrkCCEAAQgAAEIQAACEIAABCAAAQhAAAIQqEoC\nOLCq8rDQKQhAAAIQgAAEIAABCEAAAhCAAAQgAIFAAAdWIEEIAQhAAAIQgAAEIAABCEAAAhCA\nAAQgUJUEcGBV5WGhUxCAAAQgAAEIQAACEIAABCAAAQhAAAKBAA6sQIIQAhCAAAQgAAEIQAAC\nEIAABCAAAQhAoCoJ4MCqysNCpyAAAQhAAAIQgAAEIAABCEAAAhCAAAQCARxYgQQhBCAAAQhA\nAAIQgAAEIAABCEAAAhCAQFUSwIFVlYeFTkEAAhCAAAQgAAEIQAACEIAABCAAAQgEAjiwAglC\nCEAAAhCAAAQgAAEIQAACEIAABCAAgaokgAOrKg8LnYIABCAAAQhAAAIQgAAEIAABCEAAAhAI\nBHBgBRKEEIAABCAAAQhAAAIQgAAEIAABCEAAAlVJAAdWVR4WOgUBCEAAAhCAAAQgAAEIQAAC\nEIAABCAQCODACiQIIQABCEAAAhCAAAQgAAEIQAACEIAABKqSAA6sqjwsdAoCEIAABCAAAQhA\nAAIQgAAEIAABCEAgEMCBFUgQQgACEIAABCAAAQhAAAIQgAAEIAABCFQlARxYVXlY6BQEIAAB\nCEAAAhCAAAQgAAEIQAACEIBAIIADK5AghAAEIAABCEAAAhCAAAQgAAEIQAACEKhKAjiwqvKw\n0CkIQAACEIAABCAAAQhAAAIQgAAEIACBQKB3iBBCAAIQgAAEIAABCHQ6gX7awwRpuDRMapWW\nSX+T5ibbCjAIQAACEIAABCAAgZhAdzmwvqFOHBd3pEB8O6VfLn2xQD7JEIAABCAAAQhAoCcQ\n8JzrEmmqNLhAh2cr/SxpToF8kiEAAQhAAAIQgEDdEuguB9YtIv5MGdQ/pTL8zLEMUBSBAAQg\nAAEIQKCqCVyp3p0oXSHdIS2Ulkp9JTu0xktnSI9KB0mzJAwCEIAABCAAAQhAICHQXQ6sh7V/\nq5R9QAVWlipEPgQgAAEIQAACEKhiAgPVtynSJGlGRj/nKc0/IbxRukE6RcKBJQgYBCAAAQhA\nAAIQCAR4uimQIIQABCAAAQhAAAKdQ2C0mvVaV3eX0fxMlTm4jHIUgQAEIAABCEAAAnVFAAdW\nXR1uBgsBCEAAAhCAQDcQ8NNVi6VS63/6yfjJ0hMSBgEIQAACEIAABCAQEeiunxBGXSAKAQhA\nAAIQgAAEappAi0Y3TbpOOlWaLi2Qlkh9pLAG1mmKj5UmShgEIAABCEAAAhCAQEQAB1YEgygE\nIAABCEAAAhDoJAIXq12v/3mZlPUkVrPSvQbW6ZKf2MIgAAEIQAACEIAABCICOLAiGEQhAAEI\nQAACEIBAJxK4S22Pk3aQRkoDJP9ZzfxEqxRiEIAABCAAAQhAAAIZBHBgZUAhCQIQgAAEIAAB\nCHQSgX5qd4Q0RBomeXH37SXPyeYm2wowCEAAAhCAAAQgAIGYAA6smAZxCEAAAhCAAAQg0DkE\nPOe6RJoqec2rLJutxLOkOVmZpEEAAhCAAAQgAIF6JsC/ENbz0WfsEIAABCAAAQh0FYErtaPz\npaukQ6RdpKGSf044QfK/Dy6SHpUOkDAIQAACEIAABCAAgYgAT2BFMIhCAAIQgAAEIACBTiAw\nUG1OkSZJMzLan6c0L9zuRdxvkE6RZkkYBCAAAQhAAAIQgEBCgCewOBUgAAEIQAACEIBA5xIY\nrea91tXdZexmpsocXEY5ikAAAhCAAAQgAIG6IoADq64ON4OFAAQgAAEIQKAbCPjpqsXScSX2\n7Sfj/VPCJ0qUIxsCEIAABCAAAQjUHQF+Qlh3h5wBQwACEIAABCDQxQRatL9p0nXSqdJ0aYG0\nROojeVH38dJp0lhpooRBAAIQgAAEIAABCEQEcGBFMIhCAAIQgAAEIACBTiJwsdp9WLpMynoS\nq1npXgPrdMlPbGEQgAAEIAABCEAAAhEBHFgRDKIQgAAEIAABCECgEwncpbbHSf7nwZHSAGml\nND/RKoUYBCAAAQhAAAIQgEAGARxYGVBIggAEIAABCEAAAp1EoJ/aHSENkYZJXtx9e8lzsrnJ\ntgIMAhCAAAQgAAEIQCAmgAMrpkEcAhCAAAQgAAEIdA4Bz7kukaZKXvMqy2Yr8SxpTlYmaRCA\nAAQgAAEIQKCeCfAvhPV89Bk7BCAAAQhAAAJdReBK7eh86SrpEGkXaajknxNOkPzvg4ukR6UD\nJAwCEIAABCAAAQhAICLAE1gRDKIQgAAEIAABCECgEwgMVJtTpEnSjIz25ynNC7d7EfcbpFOk\nWVKl9lZV2K+MSmNU5lrJi8pjEIAABCAAAQhAoEcQwIHVIw4TnYQABCAAAQhAoAcTGK2+e62r\nu8sYw0yVOa+McllF3q3EY7IyUml2YG0l4cBKgWETAhCAAAQgAIHqJYADq3qPDT2DAAQgAAEI\nQKA2CPjpqsXScdJNRYbkeZl/SvhEkTLFsr6gTKuUPaQCXjAegwAEIAABCEAAAj2GAA6sHnOo\n6CgEIAABCEAAAj2UQIv6PU26TjpVmi4tkJZIfSQv6j5eOk0aK02UMAhAAAIQgAAEIACBiAAO\nrAgGUQhAAAIQgAAEINBJBC5Wu/7J3mWSn8RKW7MSvAbW6ZKf2MIgAAEIQAACEIAABCICOLAi\nGEQhAAEIQAACEIBAJxK4S22Pk/zPgyOlAdJKaX6iVQoxCEAAAhCAAAQgAIEMAjiwMqCQBAEI\nQAACEIAABDqRwAtq28IgAAEIQAACEIAABMokgAOrTFAUgwAEIAABCEAAAptBoFF1vRZWbP21\ncZLk9a8WSn5Ci8XVBQGDAAQgAAEIQAACaQI4sNJE2IYABCAAAQhAAAIdS2BrNfeydLJ0fdK0\nnVZ3SqOTbQdeB+uL0te9gUEAAhCAAAQgAAEIvE7A3wZiEIAABCAAAQhAAAJdS+Dn2p2fwPqo\nNFx6m/RT6WvSsRIGAQhAAAIQgAAEIBARKPYEVj+VmyB5UjVMapWWSf5nHD/e7m0MAhCAAAQg\nAAEIQKAyAtur+P7S56QfJlUXKHxA2lM6VbpNwiAAAQhAAAIQgAAEEgJZDiynXSJNlQYn5dLB\nbCWcJc1JZ7ANAQhAAAIQgAAEIFCUgL8E9HpYt2SU8k8MP5iRThIEIAABCEAAAhCoawJZPyG8\nUkTOl66SDpF2kYZK/stnP5E1WVokPSodIGEQgAAEIAABCEAAAqUJeL2rLSUv2P5HaS8pbe9S\nAv9QmKbCNgQgAAEIQAACdU8g/QTWQBGZIk2SZmTQmac0/4TwRukG6RRploRBAAIQgAAEIAAB\nCGQT8BNX6yQvzv5V6V9Sk3SZ9HvJDq39JK9/dYTkLwsxCEAAAhCAAAQgAIGIQPoJLH8z6EnW\n3VGZQtGZyji4UCbpEIAABCAAAQhAAAJ5Aq/odStpX+lsyfMsr3nl9UYt23HSOyT/C6G/KMQg\nAAEIQAACEIAABCIC6Sew/HTVYsmTqJuicumo6/nbwSfSGWxDAAIQgAAEIAABCGxCYK1SHkt0\nTZLboNBfHNq8hMN3Jf9hDgYBCEAAAhCAAAQgkCKQdmB5QdFp0nWS/wFnuuRvCJdIfaTB0njp\nNGmsNFHCIAABCEAAAhCAAAQqJxCcV67JuleV86MGBCAAAQhAAAJ1RCDtwPLQL5Yelrwug5/E\nSluzEvxo++mSn9jCIAABCEAAAhCAAAQgAAEIQAACEIAABCDQaQSyHFje2V3SOMn/PDhSGiCt\nlOYnWqUQgwAEIAABCEAAAhAoTcDrX40pXaytxHLFnmvbIgIBCEAAAhCAAAQgkCvkwDIaLyo6\nQhoiDZP8mPv2kuvMTbYVYBCAAAQgAAEIQAACRQjspbwHiuSns/ykO/9EmKbCNgQgAAEIQAAC\ndU0gy4HltEukqZLXvMqy2Uo8S5qTlUkaBCAAAQhAAAIQgEAbgQcVO1O6Qrpf+pZUzLz+KAYB\nCEAAAhCAAAQgEBHIcmD5X3BOlDzJukNaKC2V+kphEfczFH9UOkiaJWEQgAAEIAABCEAAAoUJ\nXKMs/+vgVdLXpHslDAIQgAAEIAABCECgTAJpB9ZA1ZsiTZJmZLQxT2leuN2Ptt8gnSLhwBIE\nDAIQgAAEIAABCJQgcLXyT5a+IR1QoizZEIAABCAAAQhAAAIRgbQDa7TyvNbV3VGZQtGZyjiv\nUCbpEIAABCAAAQhAAAKbEPDaVp5veQ7mf3bGIAABCEAAAhCAAATKINCYKuOnqxZLx6XS05ue\ndHkC9kQ6g20IQAACEIAABCAAgYIE/A+Dj0k4rwoiIgMCEIAABCAAAQhsSiD9BFaLikyTrpNO\nlaZLXkh0idRHCmtgnab4WGmihEEAAhCAAAQgAAEIQAACEIAABCAAAQhAoNMIpB1Y3tHF0sPS\nZVLWk1j+xtBrYJ0u+YktDAIQgAAEIAABCEAAAhCAAAQgAAEIQAACnUYgy4Hlnd0ljZN2kEZK\nA6SV0vxEqxRiEIAABCAAAQhAAAIQgAAEIAABCEAAAhDodAKFHFhhxy8oYmEQgAAEIAABCEAA\nAhCAAAQgAAEIQAACEOgWAsUcWP3UownScGmY5H8nXCb5Z4Nzk20FGAQgAAEIQAACEIAABCAA\nAQhAAAIQgAAEOo9AlgPLaZdIUyUv2p5ls5V4ljQnK5M0CEAAAhCAAAQgAAEIQAACEIAABCAA\nAQh0FIEsB9aVavxE6QrpDmmhtFTqK4V/ITxD8Uelg6RZUqXmtgaVUSmrf2VUowgEIAABCEAA\nAhCAAAQgAAEIQAACEIBArRBIO4gGamBTpEnSjIxBzlOaf0LofyG8QTpFao8D6+eqN1kqx54u\npxBlIAABCEAAAhCAAAQgAAEIQAACEIAABGqTQNqBNVrD9FpXd5cx3Jkqc14Z5bKK+OeJX8zK\nSKVdr+3HUmlsQgACEIAABCAAAQhAAAIQgAAEIAABCNQRgbQDy09XLZaOk24qwsH1/ATVE0XK\nFMtaoUyrlK1WgZZShciHAAQgAAEIQAACEIAABCAAAQhAAAIQqF0CaQeWnUXTpOukU6Xp0gJp\nidRHCmtgnab4WGmihEEAAhCAAAQgAAEIQAACEIAABCAAAQhAoNMIpB1Y3tHF0sPSZZKfxEpb\nsxK8Btbpkp/YwiAAAQhAAAIQgAAEIAABCEAAAhCAAAQg0GkEshxY3tld0jhpB2mkNEBaKc1P\ntEohBgEIQAACEIAABCAAAQhAAAIQgAAEIACBTidQyIHlHfeTRkhDpGGSF3ffXnKducm2AgwC\nEIAABCAAAQhAAAIQgAAEIAABCEAAAp1HIMuB5bRLJP9ToNe8yrLZSjxLmpOVSRoEIAABCEAA\nAhCAAAQgAAEIQAACEIAABDqKQGNGQ1cq7XzpKukQaRdpqOSfE06Q/O+Di6RHpQMkDAIQgAAE\nIAABCEAAAhCAAAQgAAEIQAACnUYg/QTWQO1pijRJmpGx13lK88LtXsT9BukUaZaEQQACEIAA\nBCAAAQiUJuAlGvyF4HApLNGwTHHPr1iiQRAwCEAAAhCAAAQgkEUg7cAarUJe6+rurMKptJna\nPi+VxiYEIAABCEAAAhCAwKYEWKJhUyakQAACEIAABCAAgbIJpB1Y/vZvsXScdFORVlzPPyV8\nokgZsiAAAQhAAAIQgAAENhDwEg0nSldId0gLpaVSX8lrjo6XzpC8RMNBEk+4CwIGAQhAAAIQ\ngMBmE9i9d+/eP2lsbGwKLbW2tjavW7cubPaYMO3AalHPp0nXSadK06UF0hKpjxQmWKcpPlaa\nKGEQgAAEIAABCEAAAoUJsERDYTbkQAACEIAABCDQuQS8rvn+J510Uq+wm5tvvrk5xHtSmHZg\nue8XSw9Ll0l+EittHqjXwDpd8hNbGAQgAAEIQAACEIBAYQIs0VCYDTkQgAAEIAABCHQygaam\npvWTJ09uc2DdfvvtzWvWrMnyB3VyTzav+UIdvkvNjpP8z4MjpQHSSml+olUKMQhAAAIQgAAE\nIACB0gT8hR9LNJTmRAkIQAACEIAABCBQkEAhB1ao8IIils0/ITxUOlx6UJojYRCAAAQgAAEI\nQAACxQmwRENxPuRCAAIQgAAEIACBkgSyHFiNqvVZ6VjpRekr0tPS3yX/3bPN/1R4qfRpb2AQ\ngAAEIAABCEAAAkUJsERDUTxkQgACEIAABCAAgeIEshxY31OVj0j3SW+R/lf6k+TF3D8q2Zl1\ntvQpabZ0s4RBAAIQgAAEIAABCBQnwBINxfmQCwEIQAACEIAABAoSSDuwtlDJ8yT/y+B1Un/p\nN5Kfxnqr5J8O2uy42lk6Q8KBJQgYBCAAAQhAAAIQKINAP5UZIQ2R/GS7n2rfXvKcbG6yrQCD\nAAQgAAEIQAACEIgJpB1YeyrTK9PbaWV7TbIj681ScF4pmrdb9HpuEieAAAQgAAEIQAACEChM\nwHOuS6Sp0uACxfwF4VkS64wWAEQyBCAAAQhAAAL1SyDtwPLPBL0GlhdrvyPBYmfWWqlB8reE\nwd6pyPNhgxACEIAABCAAAQhAoCCBK5VzonSF5DnWQmmp1FeyQ2u8dIb0qHSQNEvCIAABCEAA\nAhCAAAQSAmkHlh1SnlT9WvqpdJG0XPJTWMH8NNaXpSOlE0IiIQQgAAEIQAACEIBAJoGBSp0i\nTZJmZJSYp7S/STdKN0inSDiwBAGDAAQgAAEIQAACgYCftkrbSUqwg+ooqTmdqe3TpcOlT0q3\nShgEIAABCEAAAhCAQGECo5Xlp9jvLlykLWemYge3bRGBAAQgAAEIQAACEMgTyHJgrVbOt6Xd\nCzD6ltK98KhDDAIQgAAEIAABCECgOAE/XbVYOq54sfxC7pNV5okS5ciGAAQgAAEIQAACdUcg\n/RPCGIDXvcoy1r3KokIaBCAAAQhAAAIQyCbQouRpkpdkOFWaLnnd0SVSH2mw5DWw/C/QY6WJ\nEgYBCEAAAhCAAAQgEBEo5sCKihGFAAQgAAEIQAACENgMAher7sPSZVLWk1hetuFGyUs1+Ikt\nDAIQgAAEIAABCEAgIoADK4JBFAIQgAAEIAABCHQigbvU9jhpB2mkNEBaKc1PtEohBgEIQAAC\nEIAABCCQQQAHVgYUkiAAAQhAAAIQgEAnEnhBbVsYBCAAAQhAAAIQgECZBHBglQmKYhCAAAQg\nAAEIQKADCPRTGxOk4dIwyf9OuEzyzwbnJtsKMAhAAAIQgAAEIACBmAAOrJgGcQhAAAIQgAAE\nINA5BDznukSaKnnR9iybrcSzpDlZmaRBAAIQgAAEIACBeiaAA6uejz5jhwAEIAABCECgqwhc\nqR2dKF0h3SEtlJZKfaXwL4RnKP6odJA0S6rURqjCTmVU2kplmsooRxEIQAACEIAABCBQNQRw\nYFXNoaAjEIAABCAAAQjUKIGBGtcUaZI0I2OM85TmnxD6XwhvkE6R2uPAulT1TpXKsT3KKUQZ\nCEAAAhCAAAQgUC0EGqulI/QDAhCAAAQgAAEI1CiB0RqX17q6u4zxzVSZg8sol1XkNCX6y8lS\nsnPssawGSIMABCAAAQhAAALVSgAHVrUeGfoFAQhAAAIQgECtEPDTVYul40oMyI6nydITJcoV\ny16vzFIqVp88CEAAAhCAAAQgUJUEPFHCIAABCEAAAhCAAAQ6j0CLmp4mXSf5J37TpQXSEqmP\nFNbA8hNUY6WJEgYBCEAAAhCAAAQgEBHAgRXBIAoBCEAAAjVJwA6Bt9TgyJ7UmNqzTlINougR\nQ7pYvXxYukzKehKrWeleA+t0yU9sYRCAAAQgAAEIQAACEQEcWBEMohCAAARqlMCp+ruxH2ls\nDTU2vufX5XJ7lTGmzzY1NZ2+xRZbqHht2Nq1a3utX7/+2XXr1u1cGyOqm1HcpZGOk3aQRkoD\npJXS/ESrFGIQgAAEIAABCEAAAhkEcGBlQCEJAhCAQI0RGK1Py/2/muvtnyrVhM3Rethfz63f\ntczBNB500EG9Lrjggl5llq/6YnfeeWfummuu4R5e9Ucqs4P9lDpCGiINk7y4+/aSj+fcZFsB\nBgEIQAACEIAABCAQE2DyG9MgDgEIQKBGCQzONaw/KVcz/pvcNrkWO7Bq9GgxrBol4DnXJdJU\nyWteZdlsJZ4lzcnKJA0CEIAABCAAAQjUMwH+hbCejz5jhwAEIAABCECgqwhcqR2dL10lHSLt\nIg2V/HPCCZL/fXCR9Kh0gIRBAAIQgAAEIAABCEQEeAIrgkEUAhCAAAQgAAEIdAKBgWpzijRJ\nmpHR/jyleeF2L+J+g3SKxAL9goBBAAIQgAAEIFARgal9+vTxnKPNtGZqzfwMAwdW22ElAgEI\nQAACEIAABDqFwGi16rWu7i6j9Zkqc14Z5SgCAQhAAAIQgAAENiLQ2Nh4+A477HDgfvvtl09f\nunRp7ne/+53jazcq2EM3cGD10ANHtyEAAQhAAAIQ6DEE/HTVYuk46aYivfa8zD8lfKJIGbIg\nAAEIQAACEIBAQQJjx47Nvf/978/nz507NziwCpbvSRk4sHrS0aKvEIAABCAAAQj0RAIt6vQ0\n6TrpVGm6tEBaIvnfQb2o+3jpNGmsNFHCIAABCEAAAhCAAAQiAjiwIhhEIQABCEAAAhCAQCcR\nuFjtPixdJvlJrLQ1K8FrYJ0u+YktDAIQgAAEIAABCEAgIoADK4JBFAIQgAAEIAABCHQigbvU\n9jjJ/zw4UhogrZTmJ1qlEIMABCAAAQhAAAIQyCCAAytKmdpLAABAAElEQVQDCkkQgAAEIAAB\nCECgEwm8oLYtDAIQgAAEIAABCECgTAKNZZajGAQgAAEIQAACEIAABCAAAQhAAAIQgAAEuoUA\nT2B1C3Z2CgEIQAACEIBAHRHYSmMdU8F4l6vscxWUpygEIAABCEAAAhCoeQI4sGr+EDNACEAA\nAhCAAAS6mcBe2v8DFfTBi7lPrqA8RSEAAQhAAAIQgEDNE8CBVfOHmAFCAAIQgAAEINDNBB7U\n/s+UrpDul74lFbMFxTLJgwAEIAABCEAAAvVIoLscWHsItlXKBqtA/1KFyIcABCAAAQhAAAJV\nTuAa9a9Bukr6mnSvhEEAAhCAAAQgAAEIlEmguxxY56h/J5XRRzuwRpdRjiIQgAAEIAABCECg\n2glcrQ6eLH1DOqDaO0v/IAABCEAAAhCAQDUR6C4H1kcEwSplD6nAP0oVIh8CEIAABCAAAQj0\nEAJe28pfznkO1txD+kw3IQABCEAAAhCAQLcT6C4HVrcPnA5AAAIQgAAEIACBbiDgfxh8rBv2\nyy4hAAEIQAACEIBAjybQ2KN7T+chAAEIQAACEIAABCAAAQhAAAIQgAAEap4ADqyaP8QMEAIQ\ngAAEIAABCEAAAhCAAAQgAAEI9GwCOLB69vGj9xCAAAQgAAEIQAACEIAABCAAAQhAoOYJ4MCq\n+UPMACEAAQhAAAIQgAAEIAABCEAAAhCAQM8mgAOrZx8/eg8BCEAAAhCAAAQgAAEIQAACEIAA\nBGqeAA6smj/EDBACEIAABCAAAQhAAAIQgAAEIAABCPRsAjiwevbxo/cQgAAEIAABCEAAAhCA\nAAQgAAEIQKDmCeDAqvlDzAAhAAEIQAACEIAABCAAAQhAAAIQgEDPJoADq2cfP3oPAQhAAAIQ\ngAAEIAABCEAAAhCAAARqngAOrJo/xAwQAhCAAAQgAAEIQAACEIAABCAAAQj0bAI4sHr28aP3\nEIAABCAAAQhAAAIQgAAEIAABCECg5gngwKr5Q8wAIQABCEAAAhCAAAQgAAEIQAACEIBAzyaA\nA6tnHz96DwEIQAACEIAABCAAAQhAAAIQgAAEap4ADqyaP8QMEAIQgAAEIAABCEAAAhCAAAQg\nAAEI9GwCvXt29+k9BCAAAQhAAAIQgAAEIAABCEAAAhCoOwJ9NOK+8ahbW1sb4u1ai+PAqrUj\nynggAAEIQAACEIAABCAAAQhAAAIQqGkCDQ0NC+SwGhQPUmnPxdu1FseBVWtHlPFAAAIQgAAE\nIAABCEAAAhCAAAQgUNME5LwaeO655+bGjRuXH+f06dNzf/jDHzZ6IqvWAODAqrUjynggAAEI\nQAACEIAABCAAAQhAAAIQqHkCI0aMyI0ZMyY/zkGDNnoYqybHziLuNXlYGRQEIAABCEAAAhCA\nAAQgAAEIQAACEKgdAjiwaudYMhIIQAACEIAABCAAAQhAAAIQgAAEIFCTBHBg1eRhZVAQgAAE\nIAABCEAAAhCAAAQgAAEIQKB2CLAGVu0cS0YCAQhAAAIQgED1E+inLk6QhkvDpFZpmfQ3aW6y\nrQCDAAQgAAEIQAACEIgJ4MCKaRCHAAQgAAEIQAACnUPAc65LpKnS4AK7mK30s6Q5BfJJhgAE\nIAABCECg/gi8UUP+nBT/gs5fgNWd4cCqu0POgCEAAQhAAAIQ6AYCV2qfJ0pXSHdIC6Wlkv/u\n2g6t8dIZ0qPSQdIsCYMABCAAAQhAAAL7NzY2Tj3wwAPbnFazZs3KrVu3rqHe0ODAqrcjzngh\nAAEIQAACEOhqAgO1wynSJGlGxs7nKc0/IbxRukE6RcKBJQgYBCAAAQhAAAK51j59+jRfdNFF\nfQKLKVOmrF6xYoW/BKsrix9Bq6uBM1gIQAACEIAABCDQRQRGaz/+1vTuMvY3U2UOLqMcRSAA\nAQhAAAIQgEBdEcCBVVeHm8FCAAIQgAAEINANBPx01WLpuBL79pPxk6UnSpQjGwIQgAAEIAAB\nCNQdgWI/IeRfcurudGDAEIAABCAAAQh0AoEWtTlNuk46VZouLZCWSP45QFgD6zTFx0oTJQwC\nEIAABCAAAQhAICKQ5cByGv+SE0EiCgEIQAACEIAABDaTwMWq/7B0mZT1JFaz0r0G1umSn9jC\nIAABCEAAAhCoPwLbasjjUsN+Q2q7bjezHFj8S07dng4MHAIQgAAEIACBTiRwl9r2pHQHaaQ0\nQFopzU+0SiEGAQhAAAIQgED9Eviuhu4vs2Lzk9z+oqvuLe3A4l9y6v6UAAAEIAABCEAAAp1I\nwEs0jJCGSMMkL+6+veQ52dxkWwEGAQhAAAIQgEC9EWhsbOx72GGH5c4555z80J966qncZz7z\nGa9d3lBvLLLGm3ZgVfovOedlNUoaBCAAAQhAAAIQgMBGBDznYomGjZCwAQEIQAACEIBAmoCc\nWLmmpqZ8cu/eaZdNunR9baf/hZB/yamv489oIQABCEAAAhDoGgJeouF86SrpEGkXaajknxNO\nkPzvg4ukR6UDJAwCEIAABCAAAQhAICKQdufxLzkRHKIQgAAEIAABCECgAwiwREMHQKQJCEAA\nAhCAAATqm0DagWUa/EtOfZ8TjB4CEIAABCAAgY4lwBINHcuT1iAAAQhAAAIQqEMCWQ4sY+Bf\ncurwZGDIEIAABCAAAQh0CoF4iYabiuzB8zL/lPCJImXIggAEIAABCEAAAnVJoJADyzD4l5y6\nPCUYNAQgAAEIQAACHUyAJRo6GCjNQQACEIAABCBQfwSyHFhO419y6u9cYMQQgAAEIAABCHQe\nga5YosF/zuMvIEsZf8VdihD5EIAABCAAAQhUHYEsB5b/JedE6QrpDmmhtFTqKw2WxktnSP6X\nnIOkWRIGAQhAAAIQgAAEIFCcQGcv0fBL7f6U4l1oy322LUYEAhCAAAQgAAEI9AACaQcW/5LT\nAw4aXYQABCAAAQhAoMcS6MwlGi4Ule+VQeZqlfG6XBgEIAABCEAAAhDoMQTSDiz+JafHHDo6\nCgEIQAACEIBADyLgOVdnL9Hgp+atUvaqCjSXKkQ+BCAAAQhAAAIQqCYCXishtvhfcuL0dNyT\nMP4lJ02FbQhAAAIQgAAEIJBNwEs0nC9dJR0i7SINlXaQJkieVy2SvETDARIGAQhAAAIQgAAE\nIBARSD+Bxb/kRHCIQgACEIAABCAAgQ4gwBINHQCRJiAAAQhAAAIQqG8CaQeWaXTFv+TUN3VG\nDwEIQAACEIBAPRFgiYZ6OtqMFQIQgAAEIACBTiGQ5cDyjjr7X3I6ZTA0CgEIQAACEIAABKqQ\nQLxEw01F+scSDUXgkAUBCEAAAhCAQH0TKOTAMpXO/Jec+qbO6CEAAQhAAAIQqCcCLNFQT0eb\nsUIAAhCAAAQg0CkEshxYTuvsf8nplMHQKAQgAAEIQAACEKhSAizRUKUHhm5BAAIQgAAEINAz\nCGQ5sPwvOSdKV0h3SP475qVSX2mwNF46Q/K/5BwkzZIwCEAAAhCAAAQgAIHiBFiioTgfciEA\nAQhAAAIQgEBBAmkHVlf9S8771aODC/bq9YxRig5/fZMYBCAAAQhAAAIQ6PEEXtAILAwCEIAA\nBCAAAQhAoEwCaQdWV/1Lzpbqn51lpcz9S/exVB3yIQABCEAAAhCAQLURaFSHvBZWbP21cZLk\np9v9xLuf0JorYRCAAAQgAAEIQAACKQJp51BX/UvOT9QPq5Q9pAJ8Q1mKEvkQgAAEIAABCFQz\nga3VuZelk6Xrk47aaXWn5C8PgzUr8kXp6yGBEAIQgAAEIAABCEBgA4G0A4t/yeHMgAAEIAAB\nCEAAAp1P4OfahZ/A+qh0gzRG+i/pa9I/pdskDAIQgAAEIAABCEAgIZB2YDmZf8nh9IAABCAA\nAQhAAAKdR2B7Nb2/9Dnph8luFih8QNpTOlXCgSUIGAQgAAEIQAACEAgEshxYzuNfcgIhQghA\nAAIQgAAEINCxBFrVnJ96vyWjWf/E8IMZ6SRBAAIQgAAEIACBuiZQyIFlKP2kEdIQaZjkyZa/\nMXQdLzDqbQwCEIAABCAAAQhAoDwCXu/Kf2TjBdv/KO0l/UuK7V3aYP3PmAhxCEAAAhCAAAQg\nIAJZDiynXSJNlQZLWTZbiWdJc7IySYMABCAAAQhAAAIQaCPgL/3WSV6c/auSnVZN0mXS7yU7\ntPaTvP7VEdJkCYMABCAAAQhAAAIQiAhkObCuVP6J0hXSHZInVUulvpIdWuOlM6RHpYOkWRIG\nAQhAAAIQgAAEIJBN4BUlbyXtLu0t7ZOEfsLdT7zbjpPeIflfCG+UMAhAAAIQgAAEIACBiEDa\ngTVQeVOkSdKMqFyIzlPkb5InVv7HnFMkHFiCgEEAAhCAAAQgAIEiBNYq77FE1yTlGhSGJRn8\nBeJ3pWVJHgEEIAABCEAAArVN4CQNz8s0tVlra2uhX8G1lannSNqB5bUZPJG6uwwoM1XmvDLK\nUQQCEIAABCAAAQhAYFMCwXnlnBc2zSYFAhCAAAQgAIEaJvCrQYMGre/Xr5//2CW3YsWKptWr\nVy+q4fFu9tDSDiw/XbVY8mPsNxVp3fW8PsMTRcqQBQEIQAACEIAABCAAAQhAAAIQgAAEILAp\ngYaPfexjfSdMmJDP+dnPfpabPn26n87GChBIO7Ds+ZsmXSedKk2XFkhLpD6SH2fzGlinSWOl\niRIGAQhAAAIQgAAEIAABCEAAAhCAAAQgsCmBnRoaGr7Tq1evNv+LfirYsn79+k1LklKUQBvA\nqNTFij8s+Z9x/CRW2pqV4DWwTpf8xBYGAQhAAAIQgAAEIAABCEAAAhCAAAQgsCmBvRobG9/z\n7ne/u1fImjlzZrMcWDxtFYCUGWY5sFz1LmmctIM0UhogrZTmJ1qlEIMABCAAAQhAAAIQgAAE\nIAABCEAAAhAoQqB3794tZ599dpsD68EHH1y3Zs2avkWqkJVBoJADKxT1gqIsKhpoEEIAAhCA\nAAQgAAEIQAACEIAABCAAAQh0OYFSDqwu7xA7hAAEIAABCEAAAhCAAAQgAAEIQAACPZDAZ5qa\nmj4a91s/FVwTbxNvPwEcWO1nR00IQAACEIAABCAAAQhAAAIQgAAEIBAI7LHzzjsPO/zww/Pb\nCxcuzP361792fF0oQNh+AmkH1lZqakwFzS1X2ecqKE9RCEAAAhCAAAQgAAEIQAACEIAABCBQ\nkwRGjBiRO/TQQ/Nje+qpp4IDqybH2tWDSjuw9lIHHqigE/43wskVlKcoBCAAAQhAAAIQgAAE\nIAABCEAAAhDo6QT8x3dDUoPol9pmswMJpB1YD6rtM6UrpPulb0nFbEGxTPIgAAEIQAACEIAA\nBCAAAQhAAAIQgEAPJjCmV69eP2psbGwKY2htbW3W2laHKNzIYdXQ0PCfUIaw4wmkHVjewzVS\ng3SV9DXpXgmDAAQgAAEIQAACEIAABCAAAQhAAAL1RmB3OaqOOProoxvDwO+88047sBo+//nP\n5yZMmJBPvvbaa3PTp0/vFcoQdjyBLAeW93K1dLL0DekACYMABCAAAQhAAAIQgAAEIAABCEAA\nAnVHoHfv3uunTJnS5sD6/e9/v27NmjV99GRWTv86mOehJ7TqjktXD7iQA8v98NpWoyWXaZYw\nCEAAAhCAAAQgAAEIQAACEIAABCAAAQh0OYFiDiz/w+BjXd4jdggBCEAAAhCAAAQgAAEIQAAC\nEIAABLqewHu0y+NTux2c2mazmwgUc2B1U5fYLQQgAAEIQAACEIAABCAAAQhAAAIQ6HICk7ff\nfvtTd9lll/yOX3nlldwjjzziNcLXdXlP2OEmBHBgbYKEBAhAAAIQgAAEIAABCEAAAhCAAATq\nkEDDHnvs0fDhD384P/Snn37aDqw6xFCdQ8aBVZ3HhV5BAAIQgAAEIAABCEAAAhCAAAQg0HkE\n+qlpKzY/bYVVKQEcWFV6YOgWBCAAAQhAAAIQgAAEIAABCEAAAp1DQP8a+EJLS8uQuPWGhobn\n423i1UUAB1Z1HQ96AwEIQAACEIAABCAAAQhAAAIQgEAnE2htbR0wderU3K677prf0+233567\n9957+3Tybml+MwjgwNoMeFSFQA8jMFr9rbULcrPG9O8yjsMbVOZCqbGMsj2pyKvq7MUSi0r2\npKNGXyEAAQhAAAIQgAAEqoKAFmzPjR7tj0m53DbbbFMVfaIThQngwCrMhhwI1BKB3TSYf9TS\ngKKxvFXxB6PtrOjbevXq9bG99957fVZmT0xbs2ZNw9///vcm9f0q6bmeOAb6DAEIQAACEIAA\nBCAAgc0gMFF1t0/Vtxdqv1Rai34uOEw/D2zzf+ingy0qw3pXKVDVvtl2AKu9o/QPAhDYLAJb\nuPaPf/zjXL9+6XUKN6vdbq185plntujR3/zYSnVE427+whe+0LdUuZ6Sv3Dhwtw555zTU7pL\nPyEAAQhAAAIQgAAEINChBOSQ+l3v3r376ItqO6Ny69at6yW/1EtDhgwZNmbMmHzaq6++2jBn\nzpxeym454ogj2n6Ncc899zSvXbu2Q/tDY51PAAdW5zNmDxCoGgJ+LHaLLcry91RNn+kIBCAA\nAQhAAAIQgAAEIACBNAE5sHp96lOf6v2mN70pn/XLX/4yd/PNNzfuueeejRdccEHeWfXMM8/k\nLrzwwpydXPryt82BNXv27HVLlizxrxmwHkSg7QD2oD7TVQhAAAIQgAAEIAABCEAAAhCAAAQg\nAIE6IoADq44ONkOFAAQgAAEIQAACEIAABCAAAQhAAAI9kQA/IeyJR40+t5fAZFWstb+WaNWY\nbpUWtxcK9SAAAQhAAAIQgAAEIAABCFQxAa9h5T9uchjMn4OwOiOAA6vODngdD3eAxn691oBa\n09TUlF/QrxZY6HfbfbVQof8948paGA9jgAAEIAABCEAAAhCAAAQgkCLwDm3PkGKnlT8DrUuV\nY7PGCeDAqvEDzPDaCOT/IvWLX/xi35122qktsadHPvjBD65atGgRf//a0w8k/YcABCAAAQhA\nAAIQgEDtEtheQ/uyFPsfWvQPgrs2NjaOiIetfwZcqO23xGmKv6ayzTfddFNbfX8OYhH2FKU6\n2Gw7AepgrAwRAhCAAAQgAAEIQAACEIAABCAAga4lsLf+MfDsgw8+uO2L94ceemj9unXrWg8/\n/PCmkSNH5nujfwbMPfbYY/333nvv3AknnJBPW7hwYe5HP/pRf200d22X2Vs1EsCBVY1HpZP6\nJK/1fWp6j05qvruabW1ubv6cds5P6LrrCLBfCEAAAhCAAAQgAAEIQKAeCZypQe+QGvjWffr0\nOUhpbc4qOar0oFVj64UXXtj2J3JTp05dt3jx4t5vetObcpZt2bJldmDltOxLbs8998ynbb31\n1vmQFwiYAA6s+joP9n7Xu941cOedd66ZUd9yyy3Nzz33XO0MqGaODAOBAAQgAAEIQAACEIAA\nBHoggU/owYdP6Ymptq6vX7/+NW0MlmL/gdej6jV8+PCGLbfcMr/GsB1SckItGTFixNCJEyfm\nG1i+fHnuzjvvdFvr/YJBYHMIxCfg5rRD3R5CYLfddsu99a3+A4fasPvuu69FDqzaGAyjgAAE\nIAABCEAAAhCAAAQgsCkBP7n0Nin+/G4H0lDJ60vF5oXNR8cJijf26tVrdz0F1Sekt7a22um0\no8I3hDSHclb9Z8yYMUOOPPLIvANK60zlfvGLX+Tk0Gr57Gc/2/YElX7Wt2blypUNU6ZM6bP/\n/vvnm7juuutyN954Y84/CXzf+96XT/NntcSBld/mBQKbQyB+A2xOOz2lbj91dFBP6WwF/Vyi\nsmsrKE9RCEAAAhCAAAQgAAEIQAACEOgZBPyTvPukjf6FT06p1QMGDGjo379//gmol19+ufcr\nr7yydODAgUNGjRqVf+JpzZo1DY8//niTHFOtxx57bN4p5SHfddddzcprOf744/uEX+j84Q9/\nyP3xj38cOHTo0Na3v/3t+bIvvPBC3oHlnwC++c1vdtW89evXr0UOrF5hmxACXUGgrhxYehTy\nDq2XdFhXgO3Kfehicl1LS8upXblP9gUBCEAAAhCAAAQgAAEIQAACHU7gLK0h9XG12uZs0mfY\nFj8xdeutt7Y9AXXeeeeteumllxrPOeecvm95y4Y/7bv++utzUsMee+yRu+iii/JPW82bNy/3\n4Q9/OGcH1Omnn97W5p/+9Kd1qt9r3LhxufAE1dNPP93hg6FBCHQkgbpyYOlNO+iYY47JaR2o\njmTYrW3pr0Rz8pQPlAOrW/vBziEAAQhAAAIQgAAEIAABCNQwge00tvjzs5+G8rpQw1Nj9k/6\nDk2l9dbTUm+X2n7Cp89v/gC3TNqovpxVL2kNqfGHHnpo3lm1YsWKnNb99U/44qevUs2zCYH6\nIBC/AetixHrEMveGN2z0M98ePe6tttqqR/efzkMAAhCAAAQgAAEIQAACEGgnATt/7FiKzT9r\nS//zuteF2kZqigq2yqH0Lv1KZ1yUltPP6p7VE1Cj4kXM9S966+RvSreZU/2V+mneVsG5pKek\nFG1YuO222w712sO21157reGRRx5p8E/4zj///LYnoLSu1Fr9BG9brTXVz09B2WbNmpV76KGH\nWt74xjf65375tP/85z95B1Z+gxcI1DmBunNg1fnxZvgQgAAEIAABCEAAAhCAAAS6moCfJjpc\nansCSXE/UWSlHVBrlDZKiq2fnEWnS17TOG9yKK2Xw2gLOYa2DWkO5UB6UeWGal0oO61yKteg\ndaH6Oq5/zFvl0LZo0SI7s9YdeOCBW+y00075tL/+9a+5P//5z9tuv/32g975znfm13fSulL5\nhcld4PLLL8+X88sll1yyWv+61/TJT36yQW3kHVP+dYwWMvfP8lo+/vGP5z9rz58/PycHVr7e\nO97xjrb6eqpqvRdBt6NL9fPp+kmfHVhtZYhAAAIbE8CBtTEPtiAAAQhAAAIQgAAEIAABCNQL\nATtp8s6daMB2IA2Jth112gApfoLJ6Sul9J9kvVdOpC8qve1pI8XXyNm0ZVNTU7PiedNDTfIz\n9Xq1b9++fZSeXw9FTz/1kpZrgfBBciLlHVD6SV2DFhLvJ0dV7txzz/VaTvn611577Vo5l5r1\nVFObA+j222/P3XDDDU377ruv/zEv7+xauHBhTutE5evIAbVFqH/BBRessnNpv/32y73tbf6D\nP/0r1tq1dmDl9BO+1ve85z35tBdffLHNgRX/kkdPbtn5Fo8xX54XCECg8wgUc2D5DT9B8mOZ\nwyS/Qf0b3b9Jc5NtBRgEIAABCEAAAhCAQJkEmF+VCYpiEKgTAm/SOEelxmonz9iMtK2VFn9+\na5UzZpScQKPjsnIMLdVP4PxztzbnipxAq1XWFj8B1SKnUF9px7i+nE/Pytk0Kk5T3A6mDZ6j\nKEP7XpLxBNSCsWPHNrz//e/P99VrOH3/+9/Px3/1q1/J77NhCB/72MdWaYHxBjmX+hxyyCH5\nVrVIuf/xrmH33Xdv/fznP7+FE/1U0tSpU/P5hx12mH+2l49Pnz59vZ+O2mKLLXJhWRWNO5/H\nCwQgUJsE4gtgGKHTLpF8lfCidFk2W4lnSXOyMkmDAAQgAAEIQAACENiIAPOrjXCwAYGSBNKe\niOBA2eC9eL26Fxoa8/pmPvayXv0FfGxrtWGHSPy0kb+gXyF5baTYXD/9BJKdSltJ8RNIrt9f\nSu+rRY6UNyu9zYEkJ0+zfsq2i9I2GpccSiulAXLqeHw5OZoapRWqP3DYsGH5J5BUt0HrIOWf\nJtp5553tiHLR3DPPPNNbba6aMGHC1qNGjcqnPfnkk7k5c+Ys3W677QYcddRR+c96r776ak5P\nK/mndLkzzzwzFxxIN9988zo5gNa8973vzT+F5Abuv//+3B133DFgl112WfehD30oP9Zly5bl\nvvCFL+R3esUVV7TVv/jii1fr6aR+bnPixIn5/c+YMcNPKzVp3eHWffbZJ5+mn+rlQ14gAAEI\nbC6BLAfWlWr0ROkK6Q5pobRU8sXeDq3x0hnSo9JB0iwJgwAEIAABCEAAAhAoTID5VWE2leT4\nw396/uoP+XYsxLZaG3YqtDkQFLcDY72Uf6pDYTA7K9I/gXL90aFAEno//hBvh0Vs/gnVtnGC\n4sEBkt6/6+YdEVH51xRPO0vc152iMo7awWFHS+wAKeSAeVXl0uP32HvJ+RHza5VTY5nSPMdv\nM6Wt1k+69tSTOG39lxNlrTdVdqP9K315xhNAC1Rul7i+2vRP0Dz+NgeSnvLxE0Tz1MZGDijV\ny3oCyA4k92cjB5acMYvVxjYKPT47gHrpCaSXlTZQT+XkHUDaTU6Omjx3OXZWKc9Fc0uWLLGD\n5hX9XK3/lltuma8vZ08v6RW1N2Do0KHBgZRbsGBB/rzRWkl2IJl7Tj9ra9K4XpPzaGutrZRP\nk6OpQY6l5YMGDdr6iCOOyLNevXp120/QPv3pT+fCU0I//elP1+rpoib9LK53WBvJP4G7+uqr\nG8aPH79eDqL8Pu1A+sAHPuBd5pSm7m44hS666KJVzz33XP7nc34yyeb6cmDlNM6WSZMm5dOW\nLl2ad2B5w//Grp/s5dPvvvvuZj/BJEdZLiwi/vjjj+fz9FRTqxYSD/F86BctTp7TuZHf1nHP\nj1nscoMHbziFtO5UW1kiEIAABDqaQNtNKWl4oEI7q3y1m5GkFQpuUMZ86WOFChRJ/4byjiuS\nH7J2VOTX0pkhYXNCXWxn64YxQRdW3wBrwrQgYZN+q32nbvzHlBqQH/HV2LfSTS9/gy5Vvifk\nL1++vEmTlO+pr58s0V//Zn+Fbq6rw822RPkeka2JVx9NnM5XZ/3BqJjtq8xHPWkrVqin5ek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6TvLeV1Xbr7x5ZZ4ryh7jktr49oqfV+Py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\n6awOrDLXklazUFlMU6OUsM9bLjR3wdcaxyXz79ZwUjL+RKqdJ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/3J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\niyjwX8uDO1is0GjxAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “amount=[0.00e+00,7.45e+06)(91034)”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.width=10)\n",
    "options(repr.plot.height = 5)\n",
    "visualyEplain(dataOutliers, nrow(dataOutliers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UofJU/xG4KFyhxlep4H1GCb7bVOjyvugFmmfF+pVC5X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R5d0zfE7yjOROo7oa3DH5m6Tm3TMZVzbN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\nSUVORK5CYII=",
      "text/plain": [
       "Plot with title “amount=[0.00e+00,7.45e+06)”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "do <- dataOutliers\n",
    "do$scores <- NULL\n",
    "visualizeInstance(do, nrow(do))\n",
    "# dev.copy(pdf,'exp-inlier.pdf', width = 10, height = 7)\n",
    "# dev.off()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explanations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "explainOutlier <-function(data, model, sortedIndex){\n",
    "#     rowIndex <- sortedIndex \n",
    "    rowIndex <- as.numeric(rownames(data)[sortedIndex])\n",
    "    df <- data.frame(\n",
    "        patterns=names(which(model$partials$coverage[rowIndex,]==1)),\n",
    "        support=model$model@quality[which(model$partials$coverage[rowIndex,]==1),]\n",
    "    )\n",
    "    df <- df[order(df$support, decreasing = T), ]\n",
    "    IRdisplay::display_markdown(paste(\"Details for row:\",rowIndex)) \n",
    "    IRdisplay::display_markdown(paste(\"* Outlier score:\",round(model$scores[rowIndex], 2)))\n",
    "    IRdisplay::display_markdown(paste(\"* Matching patterns:\", nrow(df)))\n",
    "    coverage <- ncol(data)-1-model$partials$penalization[rowIndex]\n",
    "    IRdisplay::display_markdown(paste(\"* Coverage of the instance:\", coverage, \"(\", (coverage/(ncol(data)-1))*100, \"%)\"))\n",
    "    IRdisplay::display_markdown(paste(\"Frequencies of values:\")) \n",
    "    for(name in colnames(data)){\n",
    "        if(name!=\"scores\") {\n",
    "           value <- data[sortedIndex, which(name==colnames(data))]\n",
    "           IRdisplay::display_markdown(paste(\"  * \",name, \": \", value,\"-\", length(which(data[, which(name==colnames(data))]==value)) ))\n",
    "        }\n",
    "    }  \n",
    "    rownames(df) <- NULL\n",
    "    IRdisplay::display(df)\n",
    "}\n",
    "dataOutliers$scores <- NULL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "### Outlier"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "Details for row: 54000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Outlier score: 71552.57"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Matching patterns: 1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Coverage of the instance: 0 ( 0 %)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "Frequencies of values:"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  partnerTypeBroader :  Vzdělávací a výzkumné instituce - 3006"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  operationalProgrammeBroader :  5-1 - 9"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  amount :  [3.34e+09,3.34e+09) - 2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>patterns</th><th scope=col>support</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>{partnerTypeBroader=Vzdělávací a výzkumné instituce}</td><td>0.02801204                                          </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " patterns & support\\\\\n",
       "\\hline\n",
       "\t \\{partnerTypeBroader=Vzdělávací a výzkumné instituce\\} & 0.02801204                                              \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "patterns | support | \n",
       "|---|\n",
       "| {partnerTypeBroader=Vzdělávací a výzkumné instituce} | 0.02801204                                           | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  patterns                                             support   \n",
       "1 {partnerTypeBroader=Vzdělávací a výzkumné instituce} 0.02801204"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Details for the instance: 54000 \n",
      "* Outlier score: 71552.57 \n",
      "* Coverage of the instance: 1  of  3 attributes ( 33.3333333333333 %) \n",
      "* Number of matching frequent itemsets: 1 \n",
      "* Frequent itemsets (top-10):\n",
      "                                               itemset    support\n",
      "1 {partnerTypeBroader=Vzdělávací a výzkumné instituce} 0.02801204\n",
      "* Participations of attributes:\n",
      "partnerTypeBroader=Vzdělávací a výzkumné instituce \n",
      "                                          35.69894 \n",
      "                   operationalProgrammeBroader=5-1 \n",
      "                                      107311.00000 \n",
      "                        amount=[3.34e+09,3.34e+09) \n",
      "                                      107311.00000 \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<dl>\n",
       "\t<dt>$score</dt>\n",
       "\t\t<dd>71552.5663118208</dd>\n",
       "\t<dt>$coverage</dt>\n",
       "\t\t<dd>0.333333333333333</dd>\n",
       "\t<dt>$itemsets</dt>\n",
       "\t\t<dd><table>\n",
       "<thead><tr><th scope=col>itemset</th><th scope=col>support</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>{partnerTypeBroader=Vzdělávací a výzkumné instituce}</td><td>0.02801204                                          </td></tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</dd>\n",
       "\t<dt>$scores</dt>\n",
       "\t\t<dd><dl class=dl-horizontal>\n",
       "\t<dt>partnerTypeBroader=Vzdělávací a výzkumné instituce</dt>\n",
       "\t\t<dd>35.6989354624085</dd>\n",
       "\t<dt>operationalProgrammeBroader=5-1</dt>\n",
       "\t\t<dd>107311</dd>\n",
       "\t<dt>amount=[3.34e+09,3.34e+09)</dt>\n",
       "\t\t<dd>107311</dd>\n",
       "</dl>\n",
       "</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description}\n",
       "\\item[\\$score] 71552.5663118208\n",
       "\\item[\\$coverage] 0.333333333333333\n",
       "\\item[\\$itemsets] \\begin{tabular}{r|ll}\n",
       " itemset & support\\\\\n",
       "\\hline\n",
       "\t \\{partnerTypeBroader=Vzdělávací a výzkumné instituce\\} & 0.02801204                                              \\\\\n",
       "\\end{tabular}\n",
       "\n",
       "\\item[\\$scores] \\begin{description*}\n",
       "\\item[partnerTypeBroader=Vzdělávací a výzkumné instituce] 35.6989354624085\n",
       "\\item[operationalProgrammeBroader=5-1] 107311\n",
       "\\item[amount=\\{{[}\\}3.34e+09,3.34e+09)] 107311\n",
       "\\end{description*}\n",
       "\n",
       "\\end{description}\n"
      ],
      "text/markdown": [
       "$score\n",
       ":   71552.5663118208\n",
       "$coverage\n",
       ":   0.333333333333333\n",
       "$itemsets\n",
       ":   \n",
       "itemset | support | \n",
       "|---|\n",
       "| {partnerTypeBroader=Vzdělávací a výzkumné instituce} | 0.02801204                                           | \n",
       "\n",
       "\n",
       "\n",
       "$scores\n",
       ":   partnerTypeBroader=Vzdělávací a výzkumné instituce\n",
       ":   35.6989354624085operationalProgrammeBroader=5-1\n",
       ":   107311amount=[3.34e+09,3.34e+09)\n",
       ":   107311\n",
       "\n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "$score\n",
       "[1] 71552.57\n",
       "\n",
       "$coverage\n",
       "[1] 0.3333333\n",
       "\n",
       "$itemsets\n",
       "                                               itemset    support\n",
       "1 {partnerTypeBroader=Vzdělávací a výzkumné instituce} 0.02801204\n",
       "\n",
       "$scores\n",
       "partnerTypeBroader=Vzdělávací a výzkumné instituce \n",
       "                                          35.69894 \n",
       "                   operationalProgrammeBroader=5-1 \n",
       "                                      107311.00000 \n",
       "                        amount=[3.34e+09,3.34e+09) \n",
       "                                      107311.00000 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "IRdisplay::display_markdown(\"### Outlier\")\n",
    "explainOutlier(dataOutliers, model, 1)\n",
    "describeInstance(dataOutliers, model, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "### Inlier"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "Details for row: 96919"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Outlier score: 3.2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Matching patterns: 7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Coverage of the instance: 2 ( 100 %)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "Frequencies of values:"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  partnerTypeBroader :  Ostatní - 23009"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  operationalProgrammeBroader :  7-1 - 19122"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  amount :  [0.00e+00,7.45e+06) - 91034"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>patterns</th><th scope=col>support</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>{amount=[0.00e+00,7.45e+06)}                                                           </td><td>0.8483194                                                                              </td></tr>\n",
       "\t<tr><td>{partnerTypeBroader=Ostatní}                                                           </td><td>0.2144142                                                                              </td></tr>\n",
       "\t<tr><td>{partnerTypeBroader=Ostatní,amount=[0.00e+00,7.45e+06)}                                </td><td>0.1952829                                                                              </td></tr>\n",
       "\t<tr><td>{operationalProgrammeBroader=7-1}                                                      </td><td>0.1781924                                                                              </td></tr>\n",
       "\t<tr><td>{operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}                           </td><td>0.1748283                                                                              </td></tr>\n",
       "\t<tr><td>{partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1}                           </td><td>0.1502921                                                                              </td></tr>\n",
       "\t<tr><td>{partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}</td><td>0.1496026                                                                              </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " patterns & support\\\\\n",
       "\\hline\n",
       "\t \\{amount={[}0.00e+00,7.45e+06)\\}                                                            & 0.8483194                                                                                    \\\\\n",
       "\t \\{partnerTypeBroader=Ostatní\\}                                                            & 0.2144142                                                                                  \\\\\n",
       "\t \\{partnerTypeBroader=Ostatní,amount={[}0.00e+00,7.45e+06)\\}                                 & 0.1952829                                                                                    \\\\\n",
       "\t \\{operationalProgrammeBroader=7-1\\}                                                       & 0.1781924                                                                                  \\\\\n",
       "\t \\{operationalProgrammeBroader=7-1,amount={[}0.00e+00,7.45e+06)\\}                            & 0.1748283                                                                                    \\\\\n",
       "\t \\{partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1\\}                            & 0.1502921                                                                                  \\\\\n",
       "\t \\{partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount={[}0.00e+00,7.45e+06)\\} & 0.1496026                                                                                    \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "patterns | support | \n",
       "|---|---|---|---|---|---|---|\n",
       "| {amount=[0.00e+00,7.45e+06)}                                                            | 0.8483194                                                                               | \n",
       "| {partnerTypeBroader=Ostatní}                                                            | 0.2144142                                                                               | \n",
       "| {partnerTypeBroader=Ostatní,amount=[0.00e+00,7.45e+06)}                                 | 0.1952829                                                                               | \n",
       "| {operationalProgrammeBroader=7-1}                                                       | 0.1781924                                                                               | \n",
       "| {operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}                            | 0.1748283                                                                               | \n",
       "| {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1}                            | 0.1502921                                                                               | \n",
       "| {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)} | 0.1496026                                                                               | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  patterns                                                                               \n",
       "1 {amount=[0.00e+00,7.45e+06)}                                                           \n",
       "2 {partnerTypeBroader=Ostatní}                                                           \n",
       "3 {partnerTypeBroader=Ostatní,amount=[0.00e+00,7.45e+06)}                                \n",
       "4 {operationalProgrammeBroader=7-1}                                                      \n",
       "5 {operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}                           \n",
       "6 {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1}                           \n",
       "7 {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}\n",
       "  support  \n",
       "1 0.8483194\n",
       "2 0.2144142\n",
       "3 0.1952829\n",
       "4 0.1781924\n",
       "5 0.1748283\n",
       "6 0.1502921\n",
       "7 0.1496026"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Details for the instance: 96919 \n",
      "* Outlier score: 3.2 \n",
      "* Coverage of the instance: 3  of  3 attributes ( 100 %) \n",
      "* Number of matching frequent itemsets: 7 \n",
      "* Frequent itemsets (top-10):\n",
      "                                                                                  itemset\n",
      "3                                                            {amount=[0.00e+00,7.45e+06)}\n",
      "2                                                            {partnerTypeBroader=Ostatní}\n",
      "6                                 {partnerTypeBroader=Ostatní,amount=[0.00e+00,7.45e+06)}\n",
      "1                                                       {operationalProgrammeBroader=7-1}\n",
      "5                            {operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}\n",
      "4                            {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1}\n",
      "7 {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}\n",
      "    support\n",
      "3 0.8483194\n",
      "2 0.2144142\n",
      "6 0.1952829\n",
      "1 0.1781924\n",
      "5 0.1748283\n",
      "4 0.1502921\n",
      "7 0.1496026\n",
      "* Participations of attributes:\n",
      "     partnerTypeBroader=Ostatní operationalProgrammeBroader=7-1 \n",
      "                       3.194810                        3.506710 \n",
      "     amount=[0.00e+00,7.45e+06) \n",
      "                       2.206816 \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<dl>\n",
       "\t<dt>$score</dt>\n",
       "\t\t<dd>3.20427172229541</dd>\n",
       "\t<dt>$coverage</dt>\n",
       "\t\t<dd>1</dd>\n",
       "\t<dt>$itemsets</dt>\n",
       "\t\t<dd><table>\n",
       "<thead><tr><th></th><th scope=col>itemset</th><th scope=col>support</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>3</th><td>{amount=[0.00e+00,7.45e+06)}                                                           </td><td>0.8483194                                                                              </td></tr>\n",
       "\t<tr><th scope=row>2</th><td>{partnerTypeBroader=Ostatní}                                                           </td><td>0.2144142                                                                              </td></tr>\n",
       "\t<tr><th scope=row>6</th><td>{partnerTypeBroader=Ostatní,amount=[0.00e+00,7.45e+06)}                                </td><td>0.1952829                                                                              </td></tr>\n",
       "\t<tr><th scope=row>1</th><td>{operationalProgrammeBroader=7-1}                                                      </td><td>0.1781924                                                                              </td></tr>\n",
       "\t<tr><th scope=row>5</th><td>{operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}                           </td><td>0.1748283                                                                              </td></tr>\n",
       "\t<tr><th scope=row>4</th><td>{partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1}                           </td><td>0.1502921                                                                              </td></tr>\n",
       "\t<tr><th scope=row>7</th><td>{partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}</td><td>0.1496026                                                                              </td></tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</dd>\n",
       "\t<dt>$scores</dt>\n",
       "\t\t<dd><dl class=dl-horizontal>\n",
       "\t<dt>partnerTypeBroader=Ostatní</dt>\n",
       "\t\t<dd>3.19480972981439</dd>\n",
       "\t<dt>operationalProgrammeBroader=7-1</dt>\n",
       "\t\t<dd>3.50671040921921</dd>\n",
       "\t<dt>amount=[0.00e+00,7.45e+06)</dt>\n",
       "\t\t<dd>2.206816124574</dd>\n",
       "</dl>\n",
       "</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description}\n",
       "\\item[\\$score] 3.20427172229541\n",
       "\\item[\\$coverage] 1\n",
       "\\item[\\$itemsets] \\begin{tabular}{r|ll}\n",
       "  & itemset & support\\\\\n",
       "\\hline\n",
       "\t3 & \\{amount={[}0.00e+00,7.45e+06)\\}                                                            & 0.8483194                                                                                    \\\\\n",
       "\t2 & \\{partnerTypeBroader=Ostatní\\}                                                            & 0.2144142                                                                                  \\\\\n",
       "\t6 & \\{partnerTypeBroader=Ostatní,amount={[}0.00e+00,7.45e+06)\\}                                 & 0.1952829                                                                                    \\\\\n",
       "\t1 & \\{operationalProgrammeBroader=7-1\\}                                                       & 0.1781924                                                                                  \\\\\n",
       "\t5 & \\{operationalProgrammeBroader=7-1,amount={[}0.00e+00,7.45e+06)\\}                            & 0.1748283                                                                                    \\\\\n",
       "\t4 & \\{partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1\\}                            & 0.1502921                                                                                  \\\\\n",
       "\t7 & \\{partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount={[}0.00e+00,7.45e+06)\\} & 0.1496026                                                                                    \\\\\n",
       "\\end{tabular}\n",
       "\n",
       "\\item[\\$scores] \\begin{description*}\n",
       "\\item[partnerTypeBroader=Ostatní] 3.19480972981439\n",
       "\\item[operationalProgrammeBroader=7-1] 3.50671040921921\n",
       "\\item[amount=\\{{[}\\}0.00e+00,7.45e+06)] 2.206816124574\n",
       "\\end{description*}\n",
       "\n",
       "\\end{description}\n"
      ],
      "text/markdown": [
       "$score\n",
       ":   3.20427172229541\n",
       "$coverage\n",
       ":   1\n",
       "$itemsets\n",
       ":   \n",
       "| <!--/--> | itemset | support | \n",
       "|---|---|---|---|---|---|---|\n",
       "| 3 | {amount=[0.00e+00,7.45e+06)}                                                            | 0.8483194                                                                               | \n",
       "| 2 | {partnerTypeBroader=Ostatní}                                                            | 0.2144142                                                                               | \n",
       "| 6 | {partnerTypeBroader=Ostatní,amount=[0.00e+00,7.45e+06)}                                 | 0.1952829                                                                               | \n",
       "| 1 | {operationalProgrammeBroader=7-1}                                                       | 0.1781924                                                                               | \n",
       "| 5 | {operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}                            | 0.1748283                                                                               | \n",
       "| 4 | {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1}                            | 0.1502921                                                                               | \n",
       "| 7 | {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)} | 0.1496026                                                                               | \n",
       "\n",
       "\n",
       "\n",
       "$scores\n",
       ":   partnerTypeBroader=Ostatní\n",
       ":   3.19480972981439operationalProgrammeBroader=7-1\n",
       ":   3.50671040921921amount=[0.00e+00,7.45e+06)\n",
       ":   2.206816124574\n",
       "\n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "$score\n",
       "[1] 3.204272\n",
       "\n",
       "$coverage\n",
       "[1] 1\n",
       "\n",
       "$itemsets\n",
       "                                                                                  itemset\n",
       "3                                                            {amount=[0.00e+00,7.45e+06)}\n",
       "2                                                            {partnerTypeBroader=Ostatní}\n",
       "6                                 {partnerTypeBroader=Ostatní,amount=[0.00e+00,7.45e+06)}\n",
       "1                                                       {operationalProgrammeBroader=7-1}\n",
       "5                            {operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}\n",
       "4                            {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1}\n",
       "7 {partnerTypeBroader=Ostatní,operationalProgrammeBroader=7-1,amount=[0.00e+00,7.45e+06)}\n",
       "    support\n",
       "3 0.8483194\n",
       "2 0.2144142\n",
       "6 0.1952829\n",
       "1 0.1781924\n",
       "5 0.1748283\n",
       "4 0.1502921\n",
       "7 0.1496026\n",
       "\n",
       "$scores\n",
       "     partnerTypeBroader=Ostatní operationalProgrammeBroader=7-1 \n",
       "                       3.194810                        3.506710 \n",
       "     amount=[0.00e+00,7.45e+06) \n",
       "                       2.206816 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "IRdisplay::display_markdown(\"### Inlier\")\n",
    "explainOutlier(dataOutliers, model, nrow(dataOutliers))\n",
    "describeInstance(dataOutliers, model, nrow(dataOutliers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "### Instance with the highest amount"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "Details for row: 21257"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Outlier score: 38007.53"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Matching patterns: 2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "* Coverage of the instance: 1 ( 50 %)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "Frequencies of values:"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  partnerTypeBroader :  Podnikatelské subjekty - 23095"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  operationalProgrammeBroader :  1-5 - 16"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "  *  amount :  [7.44e+09,7.45e+09] - 1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>patterns</th><th scope=col>support</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>{partnerTypeBroader=Podnikatelské subjekty}</td><td>0.2152155883                               </td></tr>\n",
       "\t<tr><td>{operationalProgrammeBroader=1-5}          </td><td>0.0001490993                               </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " patterns & support\\\\\n",
       "\\hline\n",
       "\t \\{partnerTypeBroader=Podnikatelské subjekty\\} & 0.2152155883                                   \\\\\n",
       "\t \\{operationalProgrammeBroader=1-5\\}           & 0.0001490993                                   \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "patterns | support | \n",
       "|---|---|\n",
       "| {partnerTypeBroader=Podnikatelské subjekty} | 0.2152155883                                | \n",
       "| {operationalProgrammeBroader=1-5}           | 0.0001490993                                | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  patterns                                    support     \n",
       "1 {partnerTypeBroader=Podnikatelské subjekty} 0.2152155883\n",
       "2 {operationalProgrammeBroader=1-5}           0.0001490993"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Details for the instance: 21257 \n",
      "* Outlier score: 38007.53 \n",
      "* Coverage of the instance: 2  of  3 attributes ( 66.6666666666667 %) \n",
      "* Number of matching frequent itemsets: 2 \n",
      "* Frequent itemsets (top-10):\n",
      "                                      itemset      support\n",
      "2 {partnerTypeBroader=Podnikatelské subjekty} 0.2152155883\n",
      "1           {operationalProgrammeBroader=1-5} 0.0001490993\n",
      "* Participations of attributes:\n",
      "partnerTypeBroader=Podnikatelské subjekty \n",
      "                             4.646504e+00 \n",
      "          operationalProgrammeBroader=1-5 \n",
      "                             6.706937e+03 \n",
      "               amount=[7.44e+09,7.45e+09] \n",
      "                             1.073110e+05 \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<dl>\n",
       "\t<dt>$score</dt>\n",
       "\t\t<dd>38007.5280011907</dd>\n",
       "\t<dt>$coverage</dt>\n",
       "\t\t<dd>0.666666666666667</dd>\n",
       "\t<dt>$itemsets</dt>\n",
       "\t\t<dd><table>\n",
       "<thead><tr><th></th><th scope=col>itemset</th><th scope=col>support</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>2</th><td>{partnerTypeBroader=Podnikatelské subjekty}</td><td>0.2152155883                               </td></tr>\n",
       "\t<tr><th scope=row>1</th><td>{operationalProgrammeBroader=1-5}          </td><td>0.0001490993                               </td></tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</dd>\n",
       "\t<dt>$scores</dt>\n",
       "\t\t<dd><dl class=dl-horizontal>\n",
       "\t<dt>partnerTypeBroader=Podnikatelské subjekty</dt>\n",
       "\t\t<dd>4.64650357220177</dd>\n",
       "\t<dt>operationalProgrammeBroader=1-5</dt>\n",
       "\t\t<dd>6706.9375</dd>\n",
       "\t<dt>amount=[7.44e+09,7.45e+09]</dt>\n",
       "\t\t<dd>107311</dd>\n",
       "</dl>\n",
       "</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description}\n",
       "\\item[\\$score] 38007.5280011907\n",
       "\\item[\\$coverage] 0.666666666666667\n",
       "\\item[\\$itemsets] \\begin{tabular}{r|ll}\n",
       "  & itemset & support\\\\\n",
       "\\hline\n",
       "\t2 & \\{partnerTypeBroader=Podnikatelské subjekty\\} & 0.2152155883                                   \\\\\n",
       "\t1 & \\{operationalProgrammeBroader=1-5\\}           & 0.0001490993                                   \\\\\n",
       "\\end{tabular}\n",
       "\n",
       "\\item[\\$scores] \\begin{description*}\n",
       "\\item[partnerTypeBroader=Podnikatelské subjekty] 4.64650357220177\n",
       "\\item[operationalProgrammeBroader=1-5] 6706.9375\n",
       "\\item[amount=\\{{[}\\}7.44e+09,7.45e+09\\{{]}\\}] 107311\n",
       "\\end{description*}\n",
       "\n",
       "\\end{description}\n"
      ],
      "text/markdown": [
       "$score\n",
       ":   38007.5280011907\n",
       "$coverage\n",
       ":   0.666666666666667\n",
       "$itemsets\n",
       ":   \n",
       "| <!--/--> | itemset | support | \n",
       "|---|---|\n",
       "| 2 | {partnerTypeBroader=Podnikatelské subjekty} | 0.2152155883                                | \n",
       "| 1 | {operationalProgrammeBroader=1-5}           | 0.0001490993                                | \n",
       "\n",
       "\n",
       "\n",
       "$scores\n",
       ":   partnerTypeBroader=Podnikatelské subjekty\n",
       ":   4.64650357220177operationalProgrammeBroader=1-5\n",
       ":   6706.9375amount=[7.44e+09,7.45e+09]\n",
       ":   107311\n",
       "\n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "$score\n",
       "[1] 38007.53\n",
       "\n",
       "$coverage\n",
       "[1] 0.6666667\n",
       "\n",
       "$itemsets\n",
       "                                      itemset      support\n",
       "2 {partnerTypeBroader=Podnikatelské subjekty} 0.2152155883\n",
       "1           {operationalProgrammeBroader=1-5} 0.0001490993\n",
       "\n",
       "$scores\n",
       "partnerTypeBroader=Podnikatelské subjekty \n",
       "                             4.646504e+00 \n",
       "          operationalProgrammeBroader=1-5 \n",
       "                             6.706937e+03 \n",
       "               amount=[7.44e+09,7.45e+09] \n",
       "                             1.073110e+05 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "extreme <- which(rownames(dataOutliers)==which(data$certifiedEu==max(data$certifiedEu)))\n",
    "IRdisplay::display_markdown(\"### Instance with the highest amount\")\n",
    "explainOutlier(dataOutliers, model, extreme)\n",
    "describeInstance(dataOutliers, model, extreme)"
   ]
  }
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