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@alkutnikar
Created December 15, 2014 03:55
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Baby Weight Predictor
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"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"<center>Birth Weight Predictor</center>\n",
"<h4 align=\"right\">Authors: Ajay Lakshminarayanarao, Nargis Nigar, Nupur Dichwalkar, Rakesh Chada</h4>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Import relevant packages"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from sklearn import linear_model\n",
"from sklearn import neighbors\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from sklearn.tree import DecisionTreeRegressor\n",
"from sklearn.ensemble import AdaBoostRegressor\n",
"#import sklearn.metrics\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error, explained_variance_score, r2_score\n",
"from math import sqrt\n",
"import os\n",
"import sys\n",
"import warnings\n",
"from IPython.display import Image\n",
"warnings.filterwarnings('ignore')\n",
"\n",
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Reading CSV and extracting only relevant columns"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"'''\n",
"Data Citation: State Center for Health Statistics, 2009, \"North Carolina Vital Statistics -- Births 2008\", \n",
"http://hdl.handle.net/1902.29/10446 UNF:5:aTuN+uNcon8IvlxC8H84YQ== \n",
"Odum Institute for Research in Social Science [Distributor] V1 [Version]\n",
"'''\n",
"babiesDF = pd.read_csv('/home/alakshminara/Downloads/2008_birth_data.csv')\n",
"slicedDF = pd.DataFrame\n",
"trainDF = pd.DataFrame\n",
"testDF = pd.DataFrame\n",
"evalDF = pd.DataFrame"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Obtain Filtered Dataset of Relevant Columns"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"colIndex = 0\n",
"def binarizeColumn(x):\n",
" global colIndex\n",
" if x == colIndex:\n",
" return 1\n",
" else:\n",
" return 0\n",
"\n",
"def binarizeHisp(x):\n",
" if x == 'N':\n",
" return 0\n",
" else:\n",
" return 1"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### The following steps are executed as part of the below cell:\n",
"- All post-birth features are eliminated.\n",
"- Two columns - Weight (in pounds) and Weight (in ounces) are combined into a single column (WEIGHTLB) that represents the weight of the baby. This column is not considered while training the dataset.\n",
"- Columns related to Race have values in the range of 0-9. These columns are split into several columns for each particular race and it would contain binary values (0 and 1) indicating if that person belongs to that race.\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"global colIndex\n",
"global slicedDF\n",
"requiredColumns = ['SEX', 'MARITAL','FAGE', 'GAINED', 'VISITS', 'MAGE', 'FEDUC', 'MEDUC', 'TOTALP', 'BDEAD', 'TERMS', 'LOUTCOME', 'WEEKS', 'BPOUND', 'BOUNCE', 'RACEMOM', 'RACEDAD', 'HISPMOM', 'HISPDAD', 'CIGNUM', 'DRINKNUM', 'ANEMIA', 'CARDIAC', 'ACLUNG', 'DIABETES', 'HERPES', 'HYDRAM', 'HEMOGLOB', 'HYPERCH', 'HYPERPR', 'ECLAMP',\n",
" 'CERVIX','PINFANT','PRETERM','RENAL','RHSEN','UTERINE']\n",
"#requiredColumns = ['SEX', 'MARITAL','FAGE', 'MAGE', 'FEDUC', 'MEDUC', 'TOTALP', 'BDEAD', 'TERMS', 'LOUTCOME', 'WEEKS', 'BPOUND', 'BOUNCE', 'WEIGHT', 'RACEMOM', 'RACEDAD', 'HISPMOM', 'HISPDAD', 'CIGNUM', 'DRINKNUM', 'GAINED', 'ANEMIA', 'CARDIAC', 'ACLUNG', 'DIABETES', 'HERPES', 'HYDRAM', 'HEMOGLOB', 'HYPERCH', 'HYPERPR', 'ECLAMP',\n",
" #'CERVIX','PINFANT','PRETERM','RENAL','RHSEN','UTERINE']\n",
"#requiredColumns = ['SEX', 'MARITAL','FAGE', 'MAGE', 'FEDUC', 'MEDUC', 'TOTALP', 'BDEAD', 'TERMS', 'LOUTCOME', 'WEEKS', 'BPOUND', 'BOUNCE', 'WEIGHT', 'RACEMOM', 'RACEDAD', 'HISPMOM', 'HISPDAD', 'CIGNUM', 'DRINKNUM', 'GAINED', 'ANEMIA', 'CARDIAC', 'ACLUNG', 'DIABETES', 'HERPES', 'HEMOGLOB', 'HYPERCH', 'HYPERPR',\n",
" #'PINFANT','PRETERM']\n",
"slicedDF = babiesDF.ix[:,requiredColumns]\n",
"\n",
"print \"Initial number of rows present are:\", len(slicedDF)\n",
"\n",
"#Removing rows with missing weight details\n",
"slicedDF = slicedDF[slicedDF['BPOUND']!=99]\n",
"slicedDF = slicedDF[slicedDF['BOUNCE']!=99]\n",
"len(slicedDF)\n",
"\n",
"#adding a new column for weight in pounds\n",
"weightPound = slicedDF['BPOUND']\n",
"weightOunces = slicedDF['BOUNCE']\n",
"weight = weightPound.astype(np.float) + (0.0625 * weightOunces.astype(np.float))\n",
"slicedDF['WEIGHTLB'] = weight\n",
"raceColumns = ['OTHER_NON_WHITE', 'WHITE', 'BLACK', 'AMERICAN_INDIAN', 'CHINESE', 'JAPANESE', 'HAWAIIAN', 'FILIPINO', 'OTHER_ASIAN']\n",
"for race in raceColumns:\n",
" slicedDF[race + '_MOM'] = slicedDF['RACEMOM'].map(binarizeColumn)\n",
" colIndex = colIndex + 1\n",
"colIndex = 0\n",
"for race in raceColumns:\n",
" slicedDF[race + '_DAD'] = slicedDF['RACEMOM'].map(binarizeColumn)\n",
" colIndex = colIndex + 1\n",
"slicedDF['HISPMOM_BINARY'] = slicedDF['HISPMOM'].map(binarizeHisp)\n",
"slicedDF['HISPDAD_BINARY'] = slicedDF['HISPDAD'].map(binarizeHisp)\n",
"columnsToDrop = ['BPOUND','BOUNCE','RACEMOM','RACEDAD','HISPMOM','HISPDAD']\n",
"for column in columnsToDrop:\n",
" slicedDF = slicedDF.drop(column, 1)\n",
" \n",
"missing99Columns = ['MAGE','FEDUC','MEDUC','TOTALP','BDEAD','TERMS','WEEKS','CIGNUM','DRINKNUM','GAINED', 'VISITS']\n",
"#missing99Columns = ['MAGE','FEDUC','MEDUC','TOTALP','BDEAD','TERMS','WEEKS','WEIGHT','CIGNUM','DRINKNUM']\n",
"missing9Columns = ['LOUTCOME','ANEMIA','CARDIAC','ACLUNG','DIABETES','HERPES','HYDRAM','HEMOGLOB','HYPERCH','HYPERPR','ECLAMP'\n",
" ,'CERVIX','PINFANT','PRETERM','RENAL','RHSEN','UTERINE','MARITAL']\n",
"#missing9Columns = ['LOUTCOME','ANEMIA','CARDIAC','ACLUNG','DIABETES','HERPES','HEMOGLOB','HYPERCH','HYPERPR',\n",
" #'PINFANT','PRETERM']\n",
"missingValDF = slicedDF[slicedDF['FAGE']!=99]\n",
"\n",
"for col in missing99Columns:\n",
" missingValDF = missingValDF[missingValDF[col]!=99]\n",
" \n",
"for col in missing9Columns:\n",
" missingValDF = missingValDF[missingValDF[col]!=9]\n",
" \n",
"missing98Columns = ['CIGNUM','DRINKNUM']\n",
"for col in missing98Columns:\n",
" missingValDF = missingValDF[missingValDF[col]!=98]\n",
" \n",
"print \"Number of rows after all the filtering are:\",len(missingValDF)\n",
"print \"Number of features present are:\", len(missingValDF.columns)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Initial number of rows present are: 133422\n",
"Number of rows after all the filtering are:"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 68204\n",
"Number of features present are: 52\n"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"slicedDF.columns"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
"Index([u'SEX', u'MARITAL', u'FAGE', u'GAINED', u'VISITS', u'MAGE', u'FEDUC', u'MEDUC', u'TOTALP', u'BDEAD', u'TERMS', u'LOUTCOME', u'WEEKS', u'CIGNUM', u'DRINKNUM', u'ANEMIA', u'CARDIAC', u'ACLUNG', u'DIABETES', u'HERPES', u'HYDRAM', u'HEMOGLOB', u'HYPERCH', u'HYPERPR', u'ECLAMP', u'CERVIX', u'PINFANT', u'PRETERM', u'RENAL', u'RHSEN', u'UTERINE', u'WEIGHTLB', u'OTHER_NON_WHITE_MOM', u'WHITE_MOM', u'BLACK_MOM', u'AMERICAN_INDIAN_MOM', u'CHINESE_MOM', u'JAPANESE_MOM', u'HAWAIIAN_MOM', u'FILIPINO_MOM', u'OTHER_ASIAN_MOM', u'OTHER_NON_WHITE_DAD', u'WHITE_DAD', u'BLACK_DAD', u'AMERICAN_INDIAN_DAD', u'CHINESE_DAD', u'JAPANESE_DAD', u'HAWAIIAN_DAD', u'FILIPINO_DAD', u'OTHER_ASIAN_DAD', u'HISPMOM_BINARY', u'HISPDAD_BINARY'], dtype='object')"
]
}
],
"prompt_number": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Split Relevant Dataset to Training Data and Test Data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Randomly data is split into 85% training data and 15% test data."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def get_splitDF():\n",
" global missingValDF\n",
" global trainDF\n",
" global testDF\n",
" global evalDF\n",
" DF_temp = pd.DataFrame\n",
" rand_nos = np.random.rand(len(missingValDF)) < 0.85\n",
" trainDF = missingValDF[rand_nos]\n",
" testDF = missingValDF[~rand_nos]\n",
"\n",
"# rand_nos = np.random.rand(len(DF_temp)) < 0.6\n",
"# testDF = DF_temp[rand_nos]\n",
"# evalDF = DF_temp[~rand_nos]\n",
"\n",
" print 'Train(len) : {0} rows'.format(str(len(trainDF)))\n",
" print 'Test(len) : {0} rows'.format(str(len(testDF)))\n",
" #print 'Eval(len) : {0} rows'.format(str(len(evalDF)))\n",
"\n",
"get_splitDF()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Train(len) : 57978 rows\n",
"Test(len) : 10226 rows\n"
]
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"trainWeights = trainDF['WEIGHTLB']\n",
"testWeights = testDF['WEIGHTLB']\n",
"#evalWeights = evalDF['WEIGHTLB']\n",
"trainDF = trainDF.drop(['WEIGHTLB'], 1)\n",
"testDF = testDF.drop(['WEIGHTLB'], 1)\n",
"#evalDF = evalDF.drop(['WEIGHTLB','WEIGHT'], 1)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Input below Details of Sammi into the model. \n",
"- Gender of Baby: Female\n",
"- Father\u2019s Age: 27\n",
"- Mother\u2019s Age: 27\n",
"- Parity of Mother: 1\n",
"- Gestation period: 41 Weeks\n",
"- Weight Gained: 20 lbs.\n",
"- Drinks per week: 0.25\n",
"- Anaemic: True\n",
"- Ethnicity of Father: WHITE\n",
"- Ethnicity of Mother: WHITE\n",
"- Marital Status: True\n",
"- Education of Father: 12 years\n",
"- Education of Mother: 16 years\n",
"- Pre Natal Care: True\n",
"- Number of Prenatal Visits: 11"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sammiRow = [2, 1, 27, 20, 11, 27, 16, 12, 1, 0, 0, 1, 40, 0, 0.25, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"lastIndex = testDF.index[len(testDF.index) - 1]\n",
"testDF.loc[lastIndex + 1] = sammiRow\n",
"#print testDF.loc[lastIndex + 1]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"testDF.columns"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 9,
"text": [
"Index([u'SEX', u'MARITAL', u'FAGE', u'GAINED', u'VISITS', u'MAGE', u'FEDUC', u'MEDUC', u'TOTALP', u'BDEAD', u'TERMS', u'LOUTCOME', u'WEEKS', u'CIGNUM', u'DRINKNUM', u'ANEMIA', u'CARDIAC', u'ACLUNG', u'DIABETES', u'HERPES', u'HYDRAM', u'HEMOGLOB', u'HYPERCH', u'HYPERPR', u'ECLAMP', u'CERVIX', u'PINFANT', u'PRETERM', u'RENAL', u'RHSEN', u'UTERINE', u'OTHER_NON_WHITE_MOM', u'WHITE_MOM', u'BLACK_MOM', u'AMERICAN_INDIAN_MOM', u'CHINESE_MOM', u'JAPANESE_MOM', u'HAWAIIAN_MOM', u'FILIPINO_MOM', u'OTHER_ASIAN_MOM', u'OTHER_NON_WHITE_DAD', u'WHITE_DAD', u'BLACK_DAD', u'AMERICAN_INDIAN_DAD', u'CHINESE_DAD', u'JAPANESE_DAD', u'HAWAIIAN_DAD', u'FILIPINO_DAD', u'OTHER_ASIAN_DAD', u'HISPMOM_BINARY', u'HISPDAD_BINARY'], dtype='object')"
]
}
],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Verify if sammi's data got added properly\n",
"testDF.tail(5)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>SEX</th>\n",
" <th>MARITAL</th>\n",
" <th>FAGE</th>\n",
" <th>GAINED</th>\n",
" <th>VISITS</th>\n",
" <th>MAGE</th>\n",
" <th>FEDUC</th>\n",
" <th>MEDUC</th>\n",
" <th>TOTALP</th>\n",
" <th>BDEAD</th>\n",
" <th>TERMS</th>\n",
" <th>LOUTCOME</th>\n",
" <th>WEEKS</th>\n",
" <th>CIGNUM</th>\n",
" <th>DRINKNUM</th>\n",
" <th>ANEMIA</th>\n",
" <th>CARDIAC</th>\n",
" <th>ACLUNG</th>\n",
" <th>DIABETES</th>\n",
" <th>HERPES</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>133208</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 23</td>\n",
" <td> 24</td>\n",
" <td> 8</td>\n",
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" <td> 13</td>\n",
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" <td> 41</td>\n",
" <td> 40</td>\n",
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" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>133217</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> 34</td>\n",
" <td> 19</td>\n",
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" <td> 32</td>\n",
" <td> 17</td>\n",
" <td> 17</td>\n",
" <td> 6</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
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" <td> 39</td>\n",
" <td> 0</td>\n",
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" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
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" <td> 33</td>\n",
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" <td> 0</td>\n",
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" <td> 0</td>\n",
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" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>133222</th>\n",
" <td> 2</td>\n",
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" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 51 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 10,
"text": [
" SEX MARITAL FAGE GAINED VISITS MAGE FEDUC MEDUC TOTALP BDEAD \\\n",
"133208 1 1 23 24 8 23 13 12 2 0 \n",
"133209 2 1 41 40 10 41 14 16 2 0 \n",
"133217 1 1 34 19 12 32 17 17 6 0 \n",
"133221 1 1 29 33 25 26 17 13 2 0 \n",
"133222 2 1 27 20 11 27 16 12 1 0 \n",
"\n",
" TERMS LOUTCOME WEEKS CIGNUM DRINKNUM ANEMIA CARDIAC ACLUNG \\\n",
"133208 0 1 37 0 0.00 0 0 0 \n",
"133209 0 1 35 0 0.00 0 0 0 \n",
"133217 0 1 39 0 0.00 0 0 0 \n",
"133221 0 1 40 0 0.00 0 0 0 \n",
"133222 0 1 40 0 0.25 1 0 0 \n",
"\n",
" DIABETES HERPES \n",
"133208 0 0 ... \n",
"133209 0 0 ... \n",
"133217 0 0 ... \n",
"133221 0 0 ... \n",
"133222 0 0 ... \n",
"\n",
"[5 rows x 51 columns]"
]
}
],
"prompt_number": 10
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Normalize the required columns to bring them to same scale as others. This is required for models such as k-nearest neighbours so that all features are given equal consideration for the prediction."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The method below normalizes the columns using <b>z-scores</b>."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def normalizeData(df, nonStandardColumns):\n",
" for col in nonStandardColumns:\n",
" xx = df[col]\n",
" mean_xx = np.mean(df[col])\n",
" std_xx = np.std(df[col])\n",
" df[col+'_NEW'] = (df[col]-mean_xx)/std_xx\n",
" df.drop(axis=1,labels=[col], inplace=True)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 11
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"columns = ['FAGE','MAGE','FEDUC','VISITS','MEDUC','TOTALP','BDEAD','TERMS','WEEKS','CIGNUM','DRINKNUM','GAINED']\n",
"normalizeData(trainDF,columns)\n",
"normalizeData(testDF,columns)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 12
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Initial data analysis "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"trainDF.columns"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 13,
"text": [
"Index([u'SEX', u'MARITAL', u'LOUTCOME', u'ANEMIA', u'CARDIAC', u'ACLUNG', u'DIABETES', u'HERPES', u'HYDRAM', u'HEMOGLOB', u'HYPERCH', u'HYPERPR', u'ECLAMP', u'CERVIX', u'PINFANT', u'PRETERM', u'RENAL', u'RHSEN', u'UTERINE', u'OTHER_NON_WHITE_MOM', u'WHITE_MOM', u'BLACK_MOM', u'AMERICAN_INDIAN_MOM', u'CHINESE_MOM', u'JAPANESE_MOM', u'HAWAIIAN_MOM', u'FILIPINO_MOM', u'OTHER_ASIAN_MOM', u'OTHER_NON_WHITE_DAD', u'WHITE_DAD', u'BLACK_DAD', u'AMERICAN_INDIAN_DAD', u'CHINESE_DAD', u'JAPANESE_DAD', u'HAWAIIAN_DAD', u'FILIPINO_DAD', u'OTHER_ASIAN_DAD', u'HISPMOM_BINARY', u'HISPDAD_BINARY', u'FAGE_NEW', u'MAGE_NEW', u'FEDUC_NEW', u'VISITS_NEW', u'MEDUC_NEW', u'TOTALP_NEW', u'BDEAD_NEW', u'TERMS_NEW', u'WEEKS_NEW', u'CIGNUM_NEW', u'DRINKNUM_NEW', u'GAINED_NEW'], dtype='object')"
]
}
],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.figure(figsize=(11,11))\n",
"requiredColumns = [u'SEX', u'MARITAL', u'LOUTCOME', u'ANEMIA', u'WHITE_MOM', u'BLACK_MOM', u'WHITE_DAD', u'BLACK_DAD', u'HISPMOM_BINARY', u'HISPDAD_BINARY', u'FAGE_NEW', u'MAGE_NEW', u'FEDUC_NEW', u'VISITS_NEW', u'MEDUC_NEW', u'TOTALP_NEW', u'BDEAD_NEW', u'TERMS_NEW', u'WEEKS_NEW', u'CIGNUM_NEW', u'DRINKNUM_NEW', u'GAINED_NEW']\n",
"corrTrainDF = trainDF.ix[:,requiredColumns]\n",
"corrTrainDF['WEIGHT'] = trainWeights\n",
"corrDf = corrTrainDF.corr()\n",
"#replace all -ve values with +ve values\n",
"corrDf=corrDf.where(corrDf>0, corrDf * -1)\n",
"plt.imshow(corrDf, cmap='hot', interpolation='none')\n",
"plt.colorbar()\n",
"plt.xticks(range(len(corrDf)),corrDf.columns)\n",
"locs, labels = plt.xticks()\n",
"plt.setp(labels, rotation=40, ha='right')\n",
"ticks = plt.yticks(range(len(corrDf)), corrDf.columns)\n",
"plt.title('Correlation plot between different features in the data set')\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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YAvxYun0GMDu9zh4ktoQ/k055HwX81MzuA17lzd0jco/lJ8Alafm9wNnu/lid+obC/0bH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\nZGRkZGRkZGRkZGRkZGRkZGTMdfw/ArjTbtsbzzsAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0xab04cfec>"
]
}
],
"prompt_number": 50
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Effect of Smoking on Birth Weight"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"noCigList = missingValDF['WEIGHTLB'][missingValDF['CIGNUM']==0.0]\n",
"sns.distplot(noCigList, bins= 15, color = 'blue', hist=False, label= 'Non-Smokers')\n",
"#cigList = missingValDF['WEIGHTLB'][missingValDF['CIGNUM'].isin(frange(1.0,99.0,1.0))]\n",
"cigList = missingValDF['WEIGHTLB'][missingValDF['CIGNUM'] != 0.0]\n",
"sns.distplot(cigList, bins = 15, color = 'red', hist=False, label= 'Smokers')\n",
"plt.ylabel('Probability')\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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42a+tDQENAmUCVCBgPWYFBfmkpXXk888/YciQYbjdLpTqwgsvvHpS8P3mmy9xu60V9LGx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\n+MDJwoXJXFXBfo518vGMEGEbhVVKXQA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"text": [
"<matplotlib.figure.Figure at 0xab6c15ac>"
]
}
],
"prompt_number": 15
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Effect of Drinking on Birth Weight"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"noDrinkList = missingValDF['WEIGHTLB'][missingValDF['DRINKNUM']==0.0]\n",
"sns.distplot(noDrinkList, bins= 15, color = 'blue', hist=False, label= 'Non-Drinkers')\n",
"#cigList = missingValDF['WEIGHTLB'][missingValDF['CIGNUM'].isin(frange(1.0,99.0,1.0))]\n",
"drinkList = missingValDF['WEIGHTLB'][missingValDF['DRINKNUM'] != 0.0]\n",
"sns.distplot(drinkList, bins = 15, color = 'red', hist=False, label= 'Drinkers')\n",
"plt.ylabel('Probability')\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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gqNa6tda6FVa/xRPhDUuIusG52Oqv8Bavbx1kmlay6NQpQJMmkYgsNL70vtj3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\nTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0xab43b1ac>"
]
}
],
"prompt_number": 16
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Birth Weight Distribution according to Gender"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"boyList = missingValDF['WEIGHTLB'][missingValDF['SEX']== 1.0]\n",
"sns.distplot(boyList, bins= 15, color = 'blue', hist=False, label= 'Boys')\n",
"#cigList = missingValDF['WEIGHTLB'][missingValDF['CIGNUM'].isin(frange(1.0,99.0,1.0))]\n",
"girlList = missingValDF['WEIGHTLB'][missingValDF['SEX'] == 2.0]\n",
"sns.distplot(girlList, bins = 15, color = 'red', hist=False, label= 'Girls')\n",
"plt.ylabel('Probability')\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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L21V6FvE2EyosNRW/6otz62bwVyYyw4ABA/zs3u2guLgJ4xONqq7rLEIznvKU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\n",
"text": [
"<matplotlib.figure.Figure at 0xab4d490c>"
]
}
],
"prompt_number": 17
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Birth Weight Distribution according to APGAR Score"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"babiesDF = babiesDF[babiesDF['APGAR1']!=99]\n",
"ap = babiesDF['APGAR1']\n",
"ap.hist()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 18,
"text": [
"<matplotlib.axes.AxesSubplot at 0xab3e938c>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xab6de92c>"
]
}
],
"prompt_number": 18
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Based on the the histogram plotted above, we observed that the most dominant APGAR scores are 8 and 9."
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Probablity Distribution of APGAR Scores 8 and 9"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"babiesDF = babiesDF[babiesDF['APGAR1']!=99]\n",
"weightPound_x = babiesDF['BPOUND']\n",
"weightOunces_x = babiesDF['BOUNCE']\n",
"weight_x= weightPound_x.astype(np.float) + (0.0625 * weightOunces_x.astype(np.float))\n",
"babiesDF['WEIGHTLB'] = weight_x\n",
"\n",
"\n",
"apList1 = babiesDF['WEIGHTLB'][babiesDF['APGAR1']== 9.0]\n",
"sns.distplot(apList1, bins= 15, color = 'blue', hist=False, label= 'APGAR-9')\n",
"#cigList = missingValDF['WEIGHTLB'][missingValDF['CIGNUM'].isin(frange(1.0,99.0,1.0))]\n",
"apList2 = babiesDF['WEIGHTLB'][babiesDF['APGAR1']== 8.0]\n",
"sns.distplot(apList2, bins = 15, color = 'red', hist=False, label= 'APGAR-8')\n",
"plt.ylabel('Probability')\n",
"plt.xlim((0,15))\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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L4P5wKYEWLTEvbh/hqKomLS3AjKkl4wpFY8dFOCJRl1U0T6GiLiKrgn1CRJ3Q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\n",
"text": [
"<matplotlib.figure.Figure at 0xab44cc6c>"
]
}
],
"prompt_number": 19
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<center><h2> A brief overview of models and evaluation framework</h2></center>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We have used the following machine learning models on our dataset.\n",
"- Ordinary Least Squares Regression\n",
"- Ridge Regression\n",
"- K Nearest Neighbors\n",
"- Decision Trees\n",
"- Adaboost (with decision trees)\n",
"- Random Forest Regression"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For the evaluation, we show the plots of error distribution and values for the following error metrics:\n",
"- Root Mean Square Error\n",
"- R2 score\n",
"- Mean Absolute Error\n",
"- Explained Variance Score"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def frange(start, end=None, inc=None):\n",
" \"A range function, that does accept float increments...\"\n",
"\n",
" if end == None:\n",
" end = start + 0.0\n",
" start = 0.0\n",
"\n",
" if inc == None:\n",
" inc = 1.0\n",
"\n",
" L = []\n",
" while 1:\n",
" next = start + len(L) * inc\n",
" if inc > 0 and next >= end:\n",
" break\n",
" elif inc < 0 and next <= end:\n",
" break\n",
" L.append(next)\n",
" \n",
" return L"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dictny = {}"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 21
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following is our common evaluation function which is called for each machine learning model we built. It produces an error distribution plot with lines indicating mean and standard deviation. It also outputs the error metrics for Root Mean Square Error, Mean absolute error, r2 score and explained variance score."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def error_distribution(testDF, actualWeight, predictedweight, modelName, plotIndex):\n",
" #diff = 'WT_DIFF'\n",
" #plt.subplot(3, 1, plotIndex)\n",
" plt.xticks(frange(-7,7,0.5))\n",
" testDF['WT_DIFF'] = (actualWeight - predictedweight)\n",
" ax = sns.distplot(testDF['WT_DIFF'], bins=50, label='Error in Weight')\n",
" meanError = np.mean(testDF['WT_DIFF'])\n",
" #print \"Mean Error is\", meanError\n",
" stdError = np.std(testDF['WT_DIFF'])\n",
" line1_string = 'Mean'\n",
" line2_string = 'Std Dev'\n",
" #ax.set_ylim((0,1))\n",
" ax.set_xlim((-7,7)) \n",
" ax.set_title('Probablity Distribution of Error -' + modelName)\n",
" ax1 = ax.plot([meanError,meanError],[0,0.5])\n",
" pos1 = [0,0.45]\n",
" pos2 = [1,0.4]\n",
" pos3 = [-1,0.4]\n",
" ax.text(pos1[0], pos1[1], line1_string, size=9, color = 'b', ha=\"center\", va=\"center\")\n",
" ax2 = ax.plot([stdError,stdError],[0,0.5], color='r')\n",
" ax.text(pos2[0], pos2[1], line2_string, size=9, color = 'b', ha=\"center\", va=\"center\")\n",
" ax3 = ax.plot([-stdError,-stdError],[0,0.5], color='r')\n",
" ax.text(pos3[0], pos3[1], line2_string, size=9, color = 'b', ha=\"center\", va=\"center\")\n",
" ax.set_xlabel('Error in Weight')\n",
" ax.set_ylabel('Probability')\n",
" rms = sqrt(mean_squared_error(actualWeight, predictedweight))\n",
" print 'The root mean square error for', modelName, 'is', rms\n",
" r2score = r2_score(actualWeight, predictedweight)\n",
" print 'The r2 score for', modelName, 'is', r2score\n",
" evs = explained_variance_score(actualWeight, predictedweight)\n",
" mae = mean_absolute_error(actualWeight,predictedweight)\n",
" print 'The mean absolute error for', modelName, 'is', mae\n",
" print 'The explained variance score for', modelName, 'is', evs\n",
" print '\\n'\n",
" values = {}\n",
" values['RMS'] = rms\n",
" values['R2 Score'] = r2score\n",
" values['Explained Variance Score'] = evs\n",
" values['Mean Absolute Error'] = mae\n",
" dictny[modelName] = values"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 22
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Baseline Model"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Our baseline model just considers the average of all the birth weights in the data set. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Evaluation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"testDFCopy = testDF.iloc[:-1]\n",
"testDFCopy['BASELINE_WEIGHT'] = np.mean(testWeights)\n",
"testDFCopy['ACTUAL_WEIGHT'] = testWeights\n",
"error_distribution(testDFCopy, testDFCopy['ACTUAL_WEIGHT'], testDFCopy['BASELINE_WEIGHT'], 'Baseline Model', 1)\n",
"#plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The root mean square error for Baseline Model is 1.32291984088\n",
"The r2 score for Baseline Model is 0.0\n",
"The mean absolute error for Baseline Model is 0.97220959551\n",
"The explained variance score for Baseline Model is 0.0\n",
"\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
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vlSk1TqKDcTp7hqguD+DzTozr8QZKgoRKy5g3I8xQ3Kar30NJsDBHJ6upayRT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\nmZmZmZmZmZmZmZmZmZmZza//AIm+lXJFcmY2AAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0xab3b00ac>"
]
}
],
"prompt_number": 23
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Prediction on Sammi"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The prediction of baseline model on sammi is just the average of all weights in the dataset."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"Prediction for Sammi's child according to Baseline Model is\", np.mean(testWeights)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Prediction for Sammi's child according to Baseline Model is 7.29075396049\n"
]
}
],
"prompt_number": 24
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Ordinary Least Squares Regression Model"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Converting our final dataframe into a n-dimensional list. This is required for passing our data to the interpolation model."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"allRowsList = []\n",
"for idx,row in trainDF.iterrows():\n",
" currentRowList = row.values.tolist()\n",
" allRowsList.append(currentRowList)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 25
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Training the data using the OLS model."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"clf = linear_model.LinearRegression()\n",
"clf.fit(allRowsList, trainWeights)\n",
"coeffArray = clf.coef_\n",
"intercept = clf.intercept_ "
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"The co-efficients and the intercept determined by the OLS Regression are:\"\n",
"print \"-----------------Co-efficients----------------------\"\n",
"print coeffArray\n",
"print \"-----------------Intercept--------------------------\"\n",
"print intercept"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The co-efficients and the intercept determined by the OLS Regression are:\n",
"-----------------Co-efficients----------------------\n",
"[ -2.64324401e-01 -9.46291542e-02 -3.95162364e-02 -1.96473339e-02\n",
" -3.61384950e-03 -6.30246466e-02 2.81921949e-01 1.00729198e-02\n",
" -2.92342501e-01 -2.13744197e-03 -2.10690321e-01 -3.40092697e-01\n",
" -7.03164677e-01 -4.01516820e-01 9.10256701e-01 -4.65535997e-01\n",
" -1.16737419e-01 2.98949566e-02 -3.83893255e-01 2.71130745e+11\n",
" 2.92741268e+11 4.23758108e+10 1.09319270e+12 3.09732903e+11\n",
" 2.72760582e+11 2.60419102e+11 3.05935317e+11 2.14309370e+12\n",
" 2.75370368e+11 2.53759845e+11 5.04125302e+11 -5.46691589e+11\n",
" 2.36768210e+11 2.73740531e+11 2.86082011e+11 2.40565796e+11\n",
" -1.59659259e+12 1.07275572e-02 7.98256239e-03 -2.13818778e-03\n",
" 6.39154749e-02 -4.52139206e-03 3.03713866e-02 2.46337799e-02\n",
" 6.31564189e-02 -2.23707855e-02 -6.31174490e-02 7.17240110e-01\n",
" -1.14450680e-01 -4.59952617e-04 1.50837373e-01]\n",
"-----------------Intercept--------------------------\n",
"-546501113016.0\n"
]
}
],
"prompt_number": 27
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Testing the OLS Model on our test data set"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"olsPrediction = clf.predict(testDF)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 28
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Don't consider sammi's row for evaluation\n",
"testDFCopy = testDF.iloc[:-1]\n",
"testDFCopy['ACTUAL_WEIGHT'] = testWeights"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 29
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Evaluation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"testDFCopy['PREDICTED_WEIGHT_OLS'] = olsPrediction[:-1]\n",
"error_distribution(testDFCopy, testDFCopy['ACTUAL_WEIGHT'], testDFCopy['PREDICTED_WEIGHT_OLS'], 'OLS Regression', 2)\n",
"#plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The root mean square error for OLS Regression is 1.05024745116\n",
"The r2 score for OLS Regression is 0.369745126578\n",
"The mean absolute error for OLS Regression is 0.819295679126\n",
"The explained variance score for OLS Regression is 0.369745220401\n",
"\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
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RH3MAhpGDVasSrFqVAOCnPx08UH7zze7z2942BsBnHrkfL+Txi18clLnySvf/4ovjB8ru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\nAAAAAAAAq/UNPPhiPteceMUAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0xab118cec>"
]
}
],
"prompt_number": 30
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Prediction on Sammi's child"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The prediction of OLS Regression Model on Sammi is obtained by taking dot-product of the co-efficients obtained from the model with corresponding sammy's data."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"Prediction for Sammi's child according to OLS Regression is\", olsPrediction[-1]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Prediction for Sammi's child according to OLS Regression is 7.48077392578\n"
]
}
],
"prompt_number": 31
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Ridge Regression Model"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It can be observed above that the co-efficients and intercept determined by the OLS model have insanely high/low values. Ridge regression penalizes such co-efficients."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"clf = linear_model.Ridge(alpha = 0.5)\n",
"clf.fit(allRowsList, trainWeights)\n",
"coeffArray = clf.coef_\n",
"intercept = clf.intercept_"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 32
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"The co-efficients and the intercept determined by the Ridge Regression are:\"\n",
"print \"-----------------Co-efficients----------------------\"\n",
"print coeffArray\n",
"print \"-----------------Intercept--------------------------\"\n",
"print intercept"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The co-efficients and the intercept determined by the Ridge Regression are:\n",
"-----------------Co-efficients----------------------\n",
"[ -2.64230939e-01 -9.25603782e-02 -3.97775961e-02 -1.85375089e-02\n",
" -3.60427517e-03 -6.25340433e-02 2.80945863e-01 1.13101430e-02\n",
" -2.92803087e-01 1.67785825e-03 -2.09591239e-01 -3.39115795e-01\n",
" -7.01897515e-01 -3.98160694e-01 9.09463109e-01 -4.65621538e-01\n",
" -1.15863511e-01 2.93076053e-02 -3.83749460e-01 3.46046726e-02\n",
" 1.11722499e-01 -5.37182878e-02 3.69749090e-02 -4.39066612e-02\n",
" -1.33427341e-01 1.46567609e-01 -1.53793376e-02 -8.34380613e-02\n",
" 3.46046726e-02 1.11722499e-01 -5.37182878e-02 3.69749090e-02\n",
" -4.39066612e-02 -1.33427341e-01 1.46567609e-01 -1.53793376e-02\n",
" -8.34380613e-02 1.03013528e-02 8.52012271e-03 -2.19363270e-03\n",
" 6.38601926e-02 -4.48186023e-03 3.03905612e-02 2.46008475e-02\n",
" 6.30955811e-02 -2.23173492e-02 -6.28641305e-02 7.17205507e-01\n",
" -1.14436212e-01 -4.56123593e-04 1.50845125e-01]\n",
"-----------------Intercept--------------------------\n",
"7.71465659741\n"
]
}
],
"prompt_number": 33
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ridgePrediction = clf.predict(testDF)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 34
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Evaluation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"testDFCopy['PREDICTED_WEIGHT_RIDGE'] = ridgePrediction[:-1]\n",
"error_distribution(testDFCopy, testDFCopy['ACTUAL_WEIGHT'], testDFCopy['PREDICTED_WEIGHT_RIDGE'], 'Ridge Regression', 3)\n",
"#plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The root mean square error for Ridge Regression is 1.05022251513\n",
"The r2 score for Ridge Regression is 0.369775054515\n",
"The mean absolute error for Ridge Regression is 0.819280646475\n",
"The explained variance score for Ridge Regression is 0.369775158306\n",
"\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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NMRso1gX02qCLZ7uIfCD3uKpeXlLLDKNEbN2TwPdhXnPl1P4B2ua4KaKbd1sL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\nxusLSURhNlq6am4AAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0xab126b6c>"
]
}
],
"prompt_number": 36
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Prediction on Sammi's child"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As done for OLS Model, the prediction of Ridge Regression Model on Sammi is obtained by taking dot-product of the co-efficients obtained from the model with corresponding sammi's data."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"Prediction for Sammi's child according to Ridge Regression is\", ridgePrediction[-1]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Prediction for Sammi's child according to Ridge Regression is 7.48222839967\n"
]
}
],
"prompt_number": 37
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#K-nearest neighbors"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The below code is for the K-nearest neighbor model. Different values of k have been tried and the accuracy has been measured and there's no particular trend observed. Higher values of k tend to perform better, but only upto a certain limit. For example, a value of k = 10 yielded about the same RMSE as when k = 150. (But is RMSE the only indicator of model performance? How about other measures/error distribution variance with k?)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"X, y = trainDF, trainWeights\n",
"\n",
"# create the model\n",
"knn = neighbors.KNeighborsClassifier(n_neighbors=100)\n",
"\n",
"# fit the model\n",
"knn.fit(X, y)\n",
"\n",
"knnPrediction = knn.predict(testDF)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 38
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#distances,indices = knn.kneighbors(testDF,5)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 39
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Evaluation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"testDFCopy['K_NEAREST_NEIGHBOURS'] = knnPrediction[:-1]\n",
"error_distribution(testDFCopy, testDFCopy['ACTUAL_WEIGHT'], testDFCopy['K_NEAREST_NEIGHBOURS'], 'KNN Regression', 4)\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The root mean square error for KNN Regression is 1.16076833422\n",
"The r2 score for KNN Regression is 0.230118215767\n",
"The mean absolute error for KNN Regression is 0.90128716018\n",
"The explained variance score for KNN Regression is 0.233419726144\n",
"\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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3G8eBufUT57DLWTUhdrf2oI1dzJmZ/XsSmOkp3WGgK/wrdF6Ad2nn2L8L/H/G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\n",
"text": [
"<matplotlib.figure.Figure at 0xab0bd22c>"
]
}
],
"prompt_number": 40
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Prediction on Sammi's child"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"Prediction for Sammi's child according to k Nearest Neighbor Model is\", knnPrediction[-1]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Prediction for Sammi's child according to k Nearest Neighbor Model is 6.9375\n"
]
}
],
"prompt_number": 41
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Decision Tree Regression"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The below code is for the Decision Tree model. Different values of depth limits have been tried and the accuracy has been measured at each depth. A depth limit of 7 seemed to produce the most accurate results."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"resultsDict = {}\n",
"optimalPrediction = []\n",
"minRMS = 2.0\n",
"#testDFCopy = testDF.iloc[:-1]\n",
"\n",
"for depth in range(1,15):\n",
" \n",
" clf_1 = DecisionTreeRegressor(max_depth=depth)\n",
" clf_1.fit(trainDF, trainWeights)\n",
"\n",
" # Predict\n",
" decisionTreePrediction = clf_1.predict(testDF)\n",
" colName = str(depth) + '_DEC_TREE'\n",
"\n",
" testDFCopy[colName] = decisionTreePrediction[:-1]\n",
" testDFCopy['ERROR_'+colName] = testDFCopy['ACTUAL_WEIGHT'] - testDFCopy[colName] \n",
"\n",
" testDFCopy['ERROR_'+colName+'_SQUARED'] = (testDFCopy['ERROR_'+colName] * testDFCopy['ERROR_'+colName])\n",
" rms = sqrt(np.mean(testDFCopy['ERROR_'+colName+'_SQUARED']))\n",
" if rms < minRMS:\n",
" minRMS = rms\n",
" optimalPrediction = decisionTreePrediction\n",
" print \"RMS for\", depth, \"-d model is\", rms\n",
" resultsDict[depth] = rms"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"RMS for 1 -d model is 1.16333150006\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 2 -d model is 1.07706964869\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 3 -d model is 1.05443404762\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 4 -d model is 1.03836585568\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 5 -d model is 1.02856654219\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 6 -d model is 1.02184545736\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 7 -d model is 1.01479132636\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 8 -d model is 1.01588813336\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 9 -d model is 1.02052969288\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 10 -d model is 1.02739176024\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 11 -d model is 1.03271604018\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 12 -d model is 1.04377435138\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 13 -d model is 1.06010198588\n",
"RMS for"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 14 -d model is 1.07851885878\n"
]
}
],
"prompt_number": 42
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following plot shows the variation of error with depth for the decision tree regression model. It can be observed that depth = 8 produces the least RMSE value."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, axes = plt.subplots(figsize=(12,10))\n",
"axes.plot(resultsDict.keys(), resultsDict.values())\n",
"print resultsDict\n",
"plt.xlabel(\"Depth\")\n",
"plt.xticks(range(1,20))\n",
"plt.ylabel(\"RMS\")\n",
"#axes.bar(preDict.keys(), preDict.values(), align=\"center\", width=0.5, alpha=0.5)\n",
"axes.set_title(\"Decision Tree\")\n",
"print type(optimalPrediction)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"{1: 1.1633315000557234, 2: 1.0770696486919005, 3: 1.0544340476168363, 4: 1.038365855679959, 5: 1.028566542189661, 6: 1.0218454573643228, 7: 1.0147913263601824, 8: 1.0158881333586196, 9: 1.020529692882566, 10: 1.0273917602379146, 11: 1.0327160401784798, 12: 1.0437743513821485, 13: 1.0601019858846084, 14: 1.0785188587825645}\n",
"<type 'numpy.ndarray'>\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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LRLbJE0YkSZLSwpJdIl46YcSSLUmSlDhLdonwrGxJkqT0sGSXiJdure4xfpIk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\nRK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0xaaf3b86c>"
]
}
],
"prompt_number": 43
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Evaluation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"error_distribution(testDFCopy, testDFCopy['ACTUAL_WEIGHT'], optimalPrediction[:-1], 'Decision Tree Regression', 1)\n",
"#plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The root mean square error for Decision Tree Regression is 1.01479132636\n",
"The r2 score for Decision Tree Regression is 0.411581344716\n",
"The mean absolute error for Decision Tree Regression is 0.787569736144\n",
"The explained variance score for Decision Tree Regression is 0.411630306568\n",
"\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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L22oITHMG0FwsbIoCsGmPzQg2ppdiWgALgAtVdUdqg4gcp6rb/E7cnKjqJzM2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\nZZuXqurDafuPyG9VIB/WdmCnLw/u3W3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"text": [
"<matplotlib.figure.Figure at 0xaaf3b82c>"
]
}
],
"prompt_number": 44
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Decision Tree with Boosting - AdaBoost Regressor"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"rng = np.random.RandomState(1)\n",
"clf_2 = AdaBoostRegressor(DecisionTreeRegressor(max_depth=8),\n",
" n_estimators=30, random_state=rng)\n",
"clf_2.fit(trainDF, trainWeights)\n",
"\n",
"# Predict\n",
"adaBoostPrediction = clf_2.predict(testDF)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 45
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Evaluation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"testDFCopy['Adaboost'] = adaBoostPrediction[:-1]\n",
"error_distribution(testDFCopy, testDFCopy['ACTUAL_WEIGHT'], testDFCopy['Adaboost'], 'AdaBoost Regression', 2)\n",
"#plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The root mean square error for AdaBoost Regression is 1.01238529877\n",
"The r2 score for AdaBoost Regression is 0.414368268765\n",
"The mean absolute error for AdaBoost Regression is 0.790180783931\n",
"The explained variance score for AdaBoost Regression is 0.416513733348\n",
"\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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bC2+iYRw8PtA7MEpjbaSoK4DTWbqgHnA7lJkDMKaaXLOA3gO8ALwKGEv56wc2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\n",
"text": [
"<matplotlib.figure.Figure at 0xaaf6226c>"
]
}
],
"prompt_number": 46
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Prediction on Sammi's child"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"Prediction for Sammi's child according to Ridge Regression is\", adaBoostPrediction[-1]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Prediction for Sammi's child according to Ridge Regression is 7.80302209705\n"
]
}
],
"prompt_number": 65
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Random Forest Regressor"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"clf_1 = RandomForestRegressor(max_depth=10)\n",
"clf_1.fit(trainDF, trainWeights)\n",
"\n",
"# Predict\n",
"randomForestPrediction = clf_1.predict(testDF)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 66
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Evaluation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"colName = 'RandomForest'\n",
"testDFCopy[colName] = randomForestPrediction[:-1]\n",
"error_distribution(testDFCopy, testDFCopy['ACTUAL_WEIGHT'], testDFCopy['RandomForest'], 'Random Forest Regressor', 3)\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The root mean square error for Random Forest Regressor is 1.01444447093\n",
"The r2 score for Random Forest Regressor is 0.42813738421\n",
"The mean absolute error for Random Forest Regressor is 0.786987502255\n",
"The explained variance score for Random Forest Regressor is 0.428348785257\n",
"\n",
"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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45Scia/IzS74x4VMS8mhvj9HTO8iOdjfrNlzm0ds7RCgUp6Jy94qcvb1DRCJl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\nMIqBaTusUkS+CpwRfA0B81V1eZrMh4D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"text": [
"<matplotlib.figure.Figure at 0xa445ea0c>"
]
}
],
"prompt_number": 80
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Prediction on Sammi"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"Prediction for Sammi's child according to Random Forest Regression Model is\", randomForestPrediction[-1]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Prediction for Sammi's child according to Random Forest Regression Model is 7.62604259432\n"
]
}
],
"prompt_number": 81
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#Add a summary of results - all error distribution plots on a single y axis and a results table here"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pd.set_option('display.max_columns', 10)\n",
"pd.set_option('display.width', 2000)\n",
"newDF= pd.DataFrame(dictny)\n",
"newDF"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>AdaBoost Regression</th>\n",
" <th>Baseline Model</th>\n",
" <th>Decision Tree Regression</th>\n",
" <th>KNN Regression</th>\n",
" <th>OLS Regression</th>\n",
" <th>Random Forest Regressor</th>\n",
" <th>Ridge Regression</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Explained Variance Score</th>\n",
" <td> 0.414776</td>\n",
" <td> 1.110223e-16</td>\n",
" <td> 0.412378</td>\n",
" <td> 0.249032</td>\n",
" <td> 0.368765</td>\n",
" <td> 0.428349</td>\n",
" <td> 0.368765</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Mean Absolute Error</th>\n",
" <td> 0.801380</td>\n",
" <td> 9.860795e-01</td>\n",
" <td> 0.798836</td>\n",
" <td> 0.900954</td>\n",
" <td> 0.830952</td>\n",
" <td> 0.786988</td>\n",
" <td> 0.830953</td>\n",
" </tr>\n",
" <tr>\n",
" <th>R2 Score</th>\n",
" <td> 0.413123</td>\n",
" <td> 0.000000e+00</td>\n",
" <td> 0.412206</td>\n",
" <td> 0.245049</td>\n",
" <td> 0.368592</td>\n",
" <td> 0.428137</td>\n",
" <td> 0.368592</td>\n",
" </tr>\n",
" <tr>\n",
" <th>RMS</th>\n",
" <td> 1.027676</td>\n",
" <td> 1.341475e+00</td>\n",
" <td> 1.028478</td>\n",
" <td> 1.165580</td>\n",
" <td> 1.065952</td>\n",
" <td> 1.014444</td>\n",
" <td> 1.065952</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>4 rows \u00d7 7 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 82,
"text": [
" AdaBoost Regression Baseline Model Decision Tree Regression KNN Regression OLS Regression Random Forest Regressor Ridge Regression\n",
"Explained Variance Score 0.414776 1.110223e-16 0.412378 0.249032 0.368765 0.428349 0.368765\n",
"Mean Absolute Error 0.801380 9.860795e-01 0.798836 0.900954 0.830952 0.786988 0.830953\n",
"R2 Score 0.413123 0.000000e+00 0.412206 0.245049 0.368592 0.428137 0.368592\n",
"RMS 1.027676 1.341475e+00 1.028478 1.165580 1.065952 1.014444 1.065952\n",
"\n",
"[4 rows x 7 columns]"
]
}
],
"prompt_number": 82
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"Image(filename='/home/nargis/Downloads/error_part1_final.png')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"png": 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14tNPvejf3+5en5kJa9daeOCBPACCgp3U6/YTRza2A2DFiiz+/vd8AFq0cBIU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"prompt_number": 89,
"text": [
"<IPython.core.display.Image at 0xade9168c>"
]
}
],
"prompt_number": 89
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"Image(filename='/home/nargis/Downloads/error_part_2_final.png')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"png": 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OEQAA4Ibj6ekjb19/nU01WpMsXu5O6ta+ngIDA+Xt61/k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UudQ8kcSKQfyy11794dXq8XtbW1SE1N9S2XS60DaStzW2PDXeukpCQA8Htfo2vXrpAkCTU1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\n+vQBAOj1eowfP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"prompt_number": 90,
"text": [
"<IPython.core.display.Image at 0xade919cc>"
]
}
],
"prompt_number": 90
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Predicted Birth Weight of Sammi's Baby is 7lb 10oz at 41 weeks"
]
}
],
"metadata": {}
}
]
}
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