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Created on Cognitive Class Labs
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"cells": [
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"source": [
"<a href=\"https://www.bigdatauniversity.com\"><img src=\"https://ibm.box.com/shared/static/cw2c7r3o20w9zn8gkecaeyjhgw3xdgbj.png\" width=\"400\" align=\"center\"></a>\n",
"\n",
"<h1><center>K-Means Clustering</center></h1>"
]
},
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"source": [
"## Introduction\n",
"\n",
"There are many models for **clustering** out there. In this notebook, we will be presenting the model that is considered one of the simplest models amongst them. Despite its simplicity, the **K-means** is vastly used for clustering in many data science applications, especially useful if you need to quickly discover insights from **unlabeled data**. In this notebook, you will learn how to use k-Means for customer segmentation.\n",
"\n",
"Some real-world applications of k-means:\n",
"- Customer segmentation\n",
"- Understand what the visitors of a website are trying to accomplish\n",
"- Pattern recognition\n",
"- Machine learning\n",
"- Data compression\n",
"\n",
"\n",
"In this notebook we practice k-means clustering with 2 examples:\n",
"- k-means on a random generated dataset\n",
"- Using k-means for customer segmentation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h1>Table of contents</h1>\n",
"\n",
"<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
" <ul>\n",
" <li><a href=\"#random_generated_dataset\">k-Means on a randomly generated dataset</a></li>\n",
" <ol>\n",
" <li><a href=\"#setting_up_K_means\">Setting up K-Means</a></li>\n",
" <li><a href=\"#creating_visual_plot\">Creating the Visual Plot</a></li>\n",
" </ol>\n",
" <li><a href=\"#customer_segmentation_K_means\">Customer Segmentation with K-Means</a></li>\n",
" <ol>\n",
" <li><a href=\"#pre_processing\">Pre-processing</a></li>\n",
" <li><a href=\"#modeling\">Modeling</a></li>\n",
" <li><a href=\"#insights\">Insights</a></li>\n",
" </ol>\n",
" </ul>\n",
"</div>\n",
"<br>\n",
"<hr>"
]
},
{
"cell_type": "markdown",
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"source": [
"### Import libraries\n",
"Lets first import the required libraries.\n",
"Also run <b> %matplotlib inline </b> since we will be plotting in this section."
]
},
{
"cell_type": "code",
"execution_count": 1,
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"source": [
"import random \n",
"import numpy as np \n",
"import matplotlib.pyplot as plt \n",
"from sklearn.cluster import KMeans \n",
"from sklearn.datasets.samples_generator import make_blobs \n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {
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"source": [
"<h1 id=\"random_generated_dataset\">k-Means on a randomly generated dataset</h1>\n",
"Lets create our own dataset for this lab!\n"
]
},
{
"cell_type": "markdown",
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"source": [
"First we need to set up a random seed. Use <b>numpy's random.seed()</b> function, where the seed will be set to <b>0</b>"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
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"outputs": [],
"source": [
"np.random.seed(0)"
]
},
{
"cell_type": "markdown",
"metadata": {
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"source": [
"Next we will be making <i> random clusters </i> of points by using the <b> make_blobs </b> class. The <b> make_blobs </b> class can take in many inputs, but we will be using these specific ones. <br> <br>\n",
"<b> <u> Input </u> </b>\n",
"<ul>\n",
" <li> <b>n_samples</b>: The total number of points equally divided among clusters. </li>\n",
" <ul> <li> Value will be: 5000 </li> </ul>\n",
" <li> <b>centers</b>: The number of centers to generate, or the fixed center locations. </li>\n",
" <ul> <li> Value will be: [[4, 4], [-2, -1], [2, -3],[1,1]] </li> </ul>\n",
" <li> <b>cluster_std</b>: The standard deviation of the clusters. </li>\n",
" <ul> <li> Value will be: 0.9 </li> </ul>\n",
"</ul>\n",
"<br>\n",
"<b> <u> Output </u> </b>\n",
"<ul>\n",
" <li> <b>X</b>: Array of shape [n_samples, n_features]. (Feature Matrix)</li>\n",
" <ul> <li> The generated samples. </li> </ul> \n",
" <li> <b>y</b>: Array of shape [n_samples]. (Response Vector)</li>\n",
" <ul> <li> The integer labels for cluster membership of each sample. </li> </ul>\n",
"</ul>\n"
]
},
{
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"outputs": [],
"source": [
"X, y = make_blobs(n_samples=5000, centers=[[4,4], [-2, -1], [2, -3], [1, 1]], cluster_std=0.9)"
]
},
{
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"metadata": {
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"source": [
"Display the scatter plot of the randomly generated data."
]
},
{
"cell_type": "code",
"execution_count": 4,
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"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7f4aa509c7b8>"
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},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(X[:, 0], X[:, 1], marker='.')"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<h2 id=\"setting_up_K_means\">Setting up K-Means</h2>\n",
"Now that we have our random data, let's set up our K-Means Clustering."
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"The KMeans class has many parameters that can be used, but we will be using these three:\n",
"<ul>\n",
" <li> <b>init</b>: Initialization method of the centroids. </li>\n",
" <ul>\n",
" <li> Value will be: \"k-means++\" </li>\n",
" <li> k-means++: Selects initial cluster centers for k-mean clustering in a smart way to speed up convergence.</li>\n",
" </ul>\n",
" <li> <b>n_clusters</b>: The number of clusters to form as well as the number of centroids to generate. </li>\n",
" <ul> <li> Value will be: 4 (since we have 4 centers)</li> </ul>\n",
" <li> <b>n_init</b>: Number of time the k-means algorithm will be run with different centroid seeds. The final results will be the best output of n_init consecutive runs in terms of inertia. </li>\n",
" <ul> <li> Value will be: 12 </li> </ul>\n",
"</ul>\n",
"\n",
"Initialize KMeans with these parameters, where the output parameter is called <b>k_means</b>."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"button": false,
"collapsed": true,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [],
"source": [
"k_means = KMeans(init = \"k-means++\", n_clusters = 4, n_init = 12)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Now let's fit the KMeans model with the feature matrix we created above, <b> X </b>"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
},
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
" n_clusters=4, n_init=12, n_jobs=None, precompute_distances='auto',\n",
" random_state=None, tol=0.0001, verbose=0)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means.fit(X)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Now let's grab the labels for each point in the model using KMeans' <b> .labels\\_ </b> attribute and save it as <b> k_means_labels </b> "
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 3, 3, ..., 1, 0, 0], dtype=int32)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means_labels = k_means.labels_\n",
"k_means_labels"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"We will also get the coordinates of the cluster centers using KMeans' <b> .cluster&#95;centers&#95; </b> and save it as <b> k_means_cluster_centers </b>"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"button": false,
"collapsed": true,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([[-2.03743147, -0.99782524],\n",
" [ 3.97334234, 3.98758687],\n",
" [ 0.96900523, 0.98370298],\n",
" [ 1.99741008, -3.01666822]])"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means_cluster_centers = k_means.cluster_centers_\n",
"k_means_cluster_centers"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<h2 id=\"creating_visual_plot\">Creating the Visual Plot</h2>\n",
"So now that we have the random data generated and the KMeans model initialized, let's plot them and see what it looks like!"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Please read through the code and comments to understand how to plot the model."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
},
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Initialize the plot with the specified dimensions.\n",
"fig = plt.figure(figsize=(6, 4))\n",
"\n",
"# Colors uses a color map, which will produce an array of colors based on\n",
"# the number of labels there are. We use set(k_means_labels) to get the\n",
"# unique labels.\n",
"colors = plt.cm.Spectral(np.linspace(0, 1, len(set(k_means_labels))))\n",
"\n",
"# Create a plot\n",
"ax = fig.add_subplot(1, 1, 1)\n",
"\n",
"# For loop that plots the data points and centroids.\n",
"# k will range from 0-3, which will match the possible clusters that each\n",
"# data point is in.\n",
"for k, col in zip(range(len([[4,4], [-2, -1], [2, -3], [1, 1]])), colors):\n",
"\n",
" # Create a list of all data points, where the data poitns that are \n",
" # in the cluster (ex. cluster 0) are labeled as true, else they are\n",
" # labeled as false.\n",
" my_members = (k_means_labels == k)\n",
" \n",
" # Define the centroid, or cluster center.\n",
" cluster_center = k_means_cluster_centers[k]\n",
" \n",
" # Plots the datapoints with color col.\n",
" ax.plot(X[my_members, 0], X[my_members, 1], 'w', markerfacecolor=col, marker='.')\n",
" \n",
" # Plots the centroids with specified color, but with a darker outline\n",
" ax.plot(cluster_center[0], cluster_center[1], 'o', markerfacecolor=col, markeredgecolor='k', markersize=6)\n",
"\n",
"# Title of the plot\n",
"ax.set_title('KMeans')\n",
"\n",
"# Remove x-axis ticks\n",
"ax.set_xticks(())\n",
"\n",
"# Remove y-axis ticks\n",
"ax.set_yticks(())\n",
"\n",
"# Show the plot\n",
"plt.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Practice\n",
"Try to cluster the above dataset into 3 clusters. \n",
"Notice: do not generate data again, use the same dataset as above."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"k_means1 = KMeans(init = \"k-means++\", n_clusters = 3, n_init = 12)\n",
"k_means1.fit(X)\n",
"k_means_labels = k_means1.labels_\n",
"k_means_cluster_centers = k_means1.cluster_centers_\n",
"k_means_cluster_centers\n",
"\n",
"# Initialize the plot with the specified dimensions.\n",
"fig = plt.figure(figsize=(6, 4))\n",
"\n",
"# Colors uses a color map, which will produce an array of colors based on\n",
"# the number of labels there are. We use set(k_means_labels) to get the\n",
"# unique labels.\n",
"colors = plt.cm.Spectral(np.linspace(0, 1, len(set(k_means_labels))))\n",
"\n",
"# Create a plot\n",
"ax = fig.add_subplot(1, 1, 1)\n",
"\n",
"# For loop that plots the data points and centroids.\n",
"# k will range from 0-3, which will match the possible clusters that each\n",
"# data point is in.\n",
"for k, col in zip(range(len([[4,4], [-2, -1], [2, -3], [1, 1]])), colors):\n",
"\n",
" # Create a list of all data points, where the data poitns that are \n",
" # in the cluster (ex. cluster 0) are labeled as true, else they are\n",
" # labeled as false.\n",
" my_members = (k_means_labels == k)\n",
" \n",
" # Define the centroid, or cluster center.\n",
" cluster_center = k_means_cluster_centers[k]\n",
" \n",
" # Plots the datapoints with color col.\n",
" ax.plot(X[my_members, 0], X[my_members, 1], 'w', markerfacecolor=col, marker='.')\n",
" \n",
" # Plots the centroids with specified color, but with a darker outline\n",
" ax.plot(cluster_center[0], cluster_center[1], 'o', markerfacecolor=col, markeredgecolor='k', markersize=6)\n",
"\n",
"# Title of the plot\n",
"ax.set_title('KMeans')\n",
"\n",
"# Remove x-axis ticks\n",
"ax.set_xticks(())\n",
"\n",
"# Remove y-axis ticks\n",
"ax.set_yticks(())\n",
"\n",
"# Show the plot\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Double-click __here__ for the solution.\n",
"\n",
"<!-- Your answer is below:\n",
"\n",
"k_means3 = KMeans(init = \"k-means++\", n_clusters = 3, n_init = 12)\n",
"k_means3.fit(X)\n",
"fig = plt.figure(figsize=(6, 4))\n",
"colors = plt.cm.Spectral(np.linspace(0, 1, len(set(k_means3.labels_))))\n",
"ax = fig.add_subplot(1, 1, 1)\n",
"for k, col in zip(range(len(k_means3.cluster_centers_)), colors):\n",
" my_members = (k_means3.labels_ == k)\n",
" cluster_center = k_means3.cluster_centers_[k]\n",
" ax.plot(X[my_members, 0], X[my_members, 1], 'w', markerfacecolor=col, marker='.')\n",
" ax.plot(cluster_center[0], cluster_center[1], 'o', markerfacecolor=col, markeredgecolor='k', markersize=6)\n",
"plt.show()\n",
"\n",
"\n",
"-->"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<h1 id=\"customer_segmentation_K_means\">Customer Segmentation with K-Means</h1>\n",
"Imagine that you have a customer dataset, and you need to apply customer segmentation on this historical data.\n",
"Customer segmentation is the practice of partitioning a customer base into groups of individuals that have similar characteristics. It is a significant strategy as a business can target these specific groups of customers and effectively allocate marketing resources. For example, one group might contain customers who are high-profit and low-risk, that is, more likely to purchase products, or subscribe for a service. A business task is to retaining those customers. Another group might include customers from non-profit organizations. And so on.\n",
"\n",
"Lets download the dataset. To download the data, we will use **`!wget`** to download it from IBM Object Storage. \n",
"__Did you know?__ When it comes to Machine Learning, you will likely be working with large datasets. As a business, where can you host your data? IBM is offering a unique opportunity for businesses, with 10 Tb of IBM Cloud Object Storage: [Sign up now for free](http://cocl.us/ML0101EN-IBM-Offer-CC)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"button": false,
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"run_control": {
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2019-04-16 00:07:27-- https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/Cust_Segmentation.csv\n",
"Resolving s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)... 67.228.254.193\n",
"Connecting to s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)|67.228.254.193|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 34276 (33K) [text/csv]\n",
"Saving to: ‘Cust_Segmentation.csv’\n",
"\n",
"Cust_Segmentation.c 100%[=====================>] 33.47K --.-KB/s in 0.02s \n",
"\n",
"2019-04-16 00:07:27 (1.46 MB/s) - ‘Cust_Segmentation.csv’ saved [34276/34276]\n",
"\n"
]
}
],
"source": [
"!wget -O Cust_Segmentation.csv https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/Cust_Segmentation.csv"
]
},
{
"cell_type": "markdown",
"metadata": {
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"deletable": true,
"new_sheet": false,
"run_control": {
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}
},
"source": [
"### Load Data From CSV File \n",
"Before you can work with the data, you must use the URL to get the Cust_Segmentation.csv."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
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"outputs": [
{
"data": {
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" <th></th>\n",
" <th>Customer Id</th>\n",
" <th>Age</th>\n",
" <th>Edu</th>\n",
" <th>Years Employed</th>\n",
" <th>Income</th>\n",
" <th>Card Debt</th>\n",
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"text/plain": [
" Customer Id Age Edu Years Employed Income Card Debt Other Debt \\\n",
"0 1 41 2 6 19 0.124 1.073 \n",
"1 2 47 1 26 100 4.582 8.218 \n",
"2 3 33 2 10 57 6.111 5.802 \n",
"3 4 29 2 4 19 0.681 0.516 \n",
"4 5 47 1 31 253 9.308 8.908 \n",
"\n",
" Defaulted Address DebtIncomeRatio \n",
"0 0.0 NBA001 6.3 \n",
"1 0.0 NBA021 12.8 \n",
"2 1.0 NBA013 20.9 \n",
"3 0.0 NBA009 6.3 \n",
"4 0.0 NBA008 7.2 "
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"cust_df = pd.read_csv(\"Cust_Segmentation.csv\")\n",
"cust_df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h2 id=\"pre_processing\">Pre-processing</h2"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
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},
"source": [
"As you can see, __Address__ in this dataset is a categorical variable. k-means algorithm isn't directly applicable to categorical variables because Euclidean distance function isn't really meaningful for discrete variables. So, lets drop this feature and run clustering."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"button": false,
"collapsed": false,
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"outputs": [
{
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" <th>Customer Id</th>\n",
" <th>Age</th>\n",
" <th>Edu</th>\n",
" <th>Years Employed</th>\n",
" <th>Income</th>\n",
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"text/plain": [
" Customer Id Age Edu Years Employed Income Card Debt Other Debt \\\n",
"0 1 41 2 6 19 0.124 1.073 \n",
"1 2 47 1 26 100 4.582 8.218 \n",
"2 3 33 2 10 57 6.111 5.802 \n",
"3 4 29 2 4 19 0.681 0.516 \n",
"4 5 47 1 31 253 9.308 8.908 \n",
"\n",
" Defaulted DebtIncomeRatio \n",
"0 0.0 6.3 \n",
"1 0.0 12.8 \n",
"2 1.0 20.9 \n",
"3 0.0 6.3 \n",
"4 0.0 7.2 "
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = cust_df.drop('Address', axis=1)\n",
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### Normalizing over the standard deviation\n",
"Now let's normalize the dataset. But why do we need normalization in the first place? Normalization is a statistical method that helps mathematical-based algorithms to interpret features with different magnitudes and distributions equally. We use __StandardScaler()__ to normalize our dataset."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
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"collapsed": false,
"deletable": true,
"new_sheet": false,
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},
"outputs": [
{
"data": {
"text/plain": [
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},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"from sklearn.preprocessing import StandardScaler\n",
"X = df.values[:,1:]\n",
"X = np.nan_to_num(X)\n",
"Clus_dataSet = StandardScaler().fit_transform(X)\n",
"Clus_dataSet"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h2 id=\"modeling\">Modeling</h2>"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"In our example (if we didn't have access to the k-means algorithm), it would be the same as guessing that each customer group would have certain age, income, education, etc, with multiple tests and experiments. However, using the K-means clustering we can do all this process much easier.\n",
"\n",
"Lets apply k-means on our dataset, and take look at cluster labels."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"button": false,
"collapsed": false,
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},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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}
],
"source": [
"clusterNum = 3\n",
"k_means = KMeans(init = \"k-means++\", n_clusters = clusterNum, n_init = 12)\n",
"k_means.fit(X)\n",
"labels = k_means.labels_\n",
"print(labels)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<h2 id=\"insights\">Insights</h2>\n",
"We assign the labels to each row in dataframe."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"button": false,
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"outputs": [
{
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" <th>Customer Id</th>\n",
" <th>Age</th>\n",
" <th>Edu</th>\n",
" <th>Years Employed</th>\n",
" <th>Income</th>\n",
" <th>Card Debt</th>\n",
" <th>Other Debt</th>\n",
" <th>Defaulted</th>\n",
" <th>DebtIncomeRatio</th>\n",
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" <td>31</td>\n",
" <td>253</td>\n",
" <td>9.308</td>\n",
" <td>8.908</td>\n",
" <td>0.0</td>\n",
" <td>7.2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer Id Age Edu Years Employed Income Card Debt Other Debt \\\n",
"0 1 41 2 6 19 0.124 1.073 \n",
"1 2 47 1 26 100 4.582 8.218 \n",
"2 3 33 2 10 57 6.111 5.802 \n",
"3 4 29 2 4 19 0.681 0.516 \n",
"4 5 47 1 31 253 9.308 8.908 \n",
"\n",
" Defaulted DebtIncomeRatio Clus_km \n",
"0 0.0 6.3 0 \n",
"1 0.0 12.8 2 \n",
"2 1.0 20.9 0 \n",
"3 0.0 6.3 0 \n",
"4 0.0 7.2 1 "
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[\"Clus_km\"] = labels\n",
"df.head(5)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"We can easily check the centroid values by averaging the features in each cluster."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
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}
},
"outputs": [
{
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" <th>Years Employed</th>\n",
" <th>Income</th>\n",
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" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>432.468413</td>\n",
" <td>32.964561</td>\n",
" <td>1.614792</td>\n",
" <td>6.374422</td>\n",
" <td>31.164869</td>\n",
" <td>1.032541</td>\n",
" <td>2.104133</td>\n",
" <td>0.285185</td>\n",
" <td>10.094761</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>410.166667</td>\n",
" <td>45.388889</td>\n",
" <td>2.666667</td>\n",
" <td>19.555556</td>\n",
" <td>227.166667</td>\n",
" <td>5.678444</td>\n",
" <td>10.907167</td>\n",
" <td>0.285714</td>\n",
" <td>7.322222</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>402.295082</td>\n",
" <td>41.333333</td>\n",
" <td>1.956284</td>\n",
" <td>15.256831</td>\n",
" <td>83.928962</td>\n",
" <td>3.103639</td>\n",
" <td>5.765279</td>\n",
" <td>0.171233</td>\n",
" <td>10.724590</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer Id Age Edu Years Employed Income \\\n",
"Clus_km \n",
"0 432.468413 32.964561 1.614792 6.374422 31.164869 \n",
"1 410.166667 45.388889 2.666667 19.555556 227.166667 \n",
"2 402.295082 41.333333 1.956284 15.256831 83.928962 \n",
"\n",
" Card Debt Other Debt Defaulted DebtIncomeRatio \n",
"Clus_km \n",
"0 1.032541 2.104133 0.285185 10.094761 \n",
"1 5.678444 10.907167 0.285714 7.322222 \n",
"2 3.103639 5.765279 0.171233 10.724590 "
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('Clus_km').mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, lets look at the distribution of customers based on their age and income:"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
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/SUQeFJEt0f+N0f0SPe9WEVkrIhdWY69hGIYxulTrLPw9YO0xjv0mOn48ysBnVPVMnHvrEyKyDPgc8LCqLgYejm4DvA1YHP27DVdAaBiGYYwT1YrGHGDLMY5tB+Ye78Gqul9VV0d/dwEbgZnAjcA3o9O+Cbwr+vtG4FvqeBaYJCKndjcwwzCMCUy1MY0sbpAfiVm4LKqKEJF5wAXAc8BUVd0PTlhEZEp02kxg94CH7Ynu21+V1YZxmtObffXC/n3kSkVm1tdz8YzZzKqvn1A9nYyJT7Wi8STwZyJyn6r2CYSIJIHPRMdflajO4wfA/1TVzuN8aUc6MCxHWERuw7mvmDNnTiUmGMZpQ3suxx2rX+BgNkttPE7M89m/bx/P7N7N1XPncf2SpXgmHEaFVCsa/wt4GnhZRO4C9uJm/h/AtRD5yKs9gYjEcYLxHVX9YXT3QRGZHq0ypgOHovv3ALMHPHwWMKwJjareDtwOrk6jymsyjFOWUJVvvriGjnyBWXX1hBoShEomkSEMlcd27mBKppZLZ81+9SczDKrfue9FEXkD8E/An+NiIiHwa+AmVX3xeI8Xt6S4E9ioqv884NADwIeBL0X/3z/g/k+KyD3AJcDRXjeWYRivzs6OdvZ0HmVKppaNbYfY19lJCKRjMRY0NjG5Js1D27exYsbMU7pY0Bg9Xktx3/PA1SKSBhqBdlXNVfjwK3Bt1deJyG+i+/4CJxb3isitwC7g3dGxn+F6Wm3FxVNeLTvLMIwBvHy4DQFW799LV7FIJh7HE49SELDu0EGWNk8m7vsczmWZkqkdb3ONk4DXvCVWJBSVikXvY37NyHEKgDeNcL4Cn6jeOsMwAMqh0lHI01koUJ9M9d0f931qPWFr+xHOaJ5MWGU7IeP0pWrREJEFwHtw6bepIYdVVW8dDcMM42SgLZvlhb17WNd6EFVl6eQWLpk5i2m1deNtGgBzGhpoy2aJj7BZkx+tOApBmcZUehysM05Gqt3u9Ubg+7hYxiGGp9jadMU4bVh/6BDfXrsGBRqSKQR4Zvcuntr1Cu9edvaE2Ct66eQWUrEYHbk86djg7WFVlXzZtR2faPtwGxOXar8pXwAeA96vqq2jb45hnBy0Znv49to1NCRTg/bqTsfjFIIy925Yx/S6OmbVN4yJParKtvYjrD90iJp4nPOnTaclkyHh+/z++RfyxV8/gV8sUBNPIEApDOkpFWhKp7npzLPGxEbj1KBa0ViAawNigmGc1qzcu3fQtqQDSfox4p7PU7te4b1nnzsm9jy0Yyu/2LqVhOcTEvLIjm3ctvxi5k9q5A3zF/JS60Ge2rWLrmhzI0+EqZlaPrHiUusma1RFtaKxCdvS1TBY13qQhuTQkF4/jak0Lx06yHvHwJbOQp6Htm1nem1d394THfkcD2zeyKcuuZyY5/Hx5Zdy0bSZPLlrJ53FIgsaG3nT/IUsarKfs1Ed1YrGZ4F/EZHnVHX7iTDIME4GVPWYaYAAIkI4Rra0ZbMgDNqsqCGZYk9np7NThGQsxtXz5nP1vPljZJVxqvJaKsKbgY0isgW3AdNAVFWvGQ3DDGMic0bzZJ7ds3tE9xRAez7HGc2Tx8SWyTU1qCrlMOwTjqOFvPWVMk4I1ZaABsBmXCuR1uj2wH9jNbkyjHHlkpmzCTSkEJSHHSuHAflymSvnHLfp86hRn0zx5vkL2d/dxaGebvZ3d5Evl7lhydIxef0Twf6uLu7b8BLb24fOS8eWfLlEa7aHcmhDWy/VthG59gTZYRgnFdPr6nj3snO4d/06EjGfxmQaEaE9nyNfLvOOxUtY0Ng0Zva8ZeEi5jc2sb71IOl4nAumTT+pK7zv37yRDa2H2NTWyl9d/YZxsWHX0Q7uXL2SXLnMtNo6brtoBbWJxLjYMpF4VdGIivkqxmIdxunCxTNnMb22jqd2v8L6QwcJgSXNk7lqztwxFQxwMZTFzc0sbj41AtvLWlrYeuQwZ7VMHTcb/nvTBkCYUVfP3q6jPLtnF29esGjc7JkoVLLS2EplRXsSnTe89NQwTlFmNzRwS8PYpNWeTlw9dz6XzJxNYoRK9rGiN0bkkh6EYmAuKqhMNKxJoGGMMy8fbuPnW1/mQHc3i5qaeMfiMyZMq5ITxXhXqV85ey5fePIxeopFZtTVceF02zQUKhANVf3mq51jGMaJY0/nUe5YvZJMPMHkdA3bj7Tznyuf508vv8p87CeQlw4dZGFTE3XxBB2FAluPHD7lhboSrIG+YUxwntmzi5jn0ZBK4XseLZkM3cUiG1oPvfqDjddMazbLlJpammsyZOJx2nP58TZpQmCiYRgTnK5Ckbg32LcvIuTKpXGy6PTg8tlzaMv2sKfzKAqcO3XaeJs0IbDWloYxwTlv2jReaj1IQyqFJ0IpCFBVawEyCmi0j8hIRZBXzZnLlEyGI7kscyc1MrOufqzNm5CYaBjGBOf8qdPZ3n6E5/fu7Wtd8s4zlp7Wg1hY3AD5/wYUUu/ES1SfwabBYbTnv0BqoPZ/4DYj7UdEWDq5ZZQsPnUw0TCMCY7vebx72TlcO28BR/N5pmQyg3bh60WDVrT0IkgKSaxAZOJ2r1XNgQYgmapbnWjYCbnvgNQBArl70NhsxGuszohgD4QHAQ+CVojNqe7xpykmGoZxktBSk6GlJjPiMQ2Pot3/DrjBWEsbIfPRcek9pVqC8AhILeINtzcsrITcD4EQEpdB+p3V2ak9oCF4NdETdkDYDdWKRnwJJK50Kw1/ZnWPPY0x0TCMU4FgD2gO/BmgCuVtoFmQkUXmRBEWN0H+XgjzIKCJK5HUdYi4nBvVnBMMrwmIQfFpSJwLsSq673qT3XUGu9xtfwb41VeOi6SRmpuqftzpjomGYZwkaLDfzeD96Yg3pE2JNADqhEIL4NXBGLunNDwKuW87t5E/ybmfCo+g3lQkeVHvReD6msYgEhJ0eNPH4yESh8ytaOklIETi5yBi9SpjhYmGYZwEhMV1kL0LEJAE1P4h4g+oUPYngz8bCg85d0vNhxjzjj7lbU4Aet1G4jsxK70AvaIhGeeSKj7tbsfmun9VIl4Nkrx4lAx/7WiwH+35GnjTkcwHnaCd4phoGMbJQOERkHq3gggOoMUXkPQ7AZc2qj13O3dN4grQEhQeQr1JSPLSMTTSh2FbU4UwYCAVEUi/07mktAyxuSOuEjRoQ0srkdjZSGzWiTX7daClbRC2RnGVo068T3FMNAzjZEBqQdtAa4EyDEwPDQ9BeRN4M0HEuaXUd0IzlqIRWwiSgvIOCHPgJUFiEL+s7xRVhWAXWt4BlBFKaGzxsBm65n4E5ZdQ7zdI/efG7hqqRBLnosEu8KeAd3rUzZhoGMYJRoPDaGk1BAfBn4rEL0T86gYYSV+P9nwdwv0Qm48kLh/wAnnAc4LRRwL0UN92r6OJBofca/rTBq0SxKtFU2+Bzi+5uEoIJN6KxM90jwuPoj13RQFsDxBUAreCqvkgMjDlNTYPypurC5CPA+LVI5nfHW8zxhQTDcN4nagWXfYSCv5MRPprKMLieldToOpm4aX1aOFRNP1+vMRZ0eNDtLgGSs8DMUhchsTPGjTYiz8V6v7MDdZSM1gI/OludRH2QG+Kq7ZC/JxRF4yw8DTk7gcE/FlQ+9FB14t2Q+xs56bRACSPiKBaRHvudIF8b8ZggQs7XZFd7aeQXvdO4nIXUI+dMar2G68fEw3DeB2ExdWQeyAazAXw0dR1SOIKV0+Q+64LBnsD3Emag9zdaOzziJdB87+IYhaTgBCy30DT70KSVw56LRF/xBRakQRa837IfhuCo+5OfyqSevuoXqtqAPmfgNfigvHBK1DaDInz+k/ypoOUQIugRyEWCWNpY7TSGqEewquH8ABafLovTkP+R1B8Afz5UPfHo3odxuvDRMMwXiNa3grZe1zdQG8KrBYh9yNUMq4ATcuDBQNcPCI8AuWX0dgSKP46ikdE2U6ahvxDaOJSRCr7iXrxxWj956G8yw3o/hwnMqOKE0WX2hvtyyaDe55K/Bw09U4orQJ/PpK63h0orXJZXcd86mYoPo+mbohWR3H3ehO4qv10xUTDMF4jmn/IzfwHumckAdIE+YcgcTHDs4kGPD7sRrTHDcCDutgmoqB3wQWSK0QkDfFju3NUS2jxeQjbXG1DrKqdnBHx0PRvQ+4+53qKLR3mPhIRJHU1pK4e/OAwixOCYxFzWV8EQAxJ3wiJC5wraxxRzUfV5pMqFvDqXyME7QBJD+t/NREx0TCM10rwCsgIlcheLYT7wD9+Wwvxp7oVipcZEo84GsUpBs/Mw/I+CPZBfBGeN2nY86mqe12pGbEPk+Z+HNVHpNDCM1D78cHB5wrwEheisUXOHec1V76a8adDeACoHfm4ZsFr7BuYRRIQG9/9uLW8yyUfREF/Mrci3jHsfz2vkb0Hgt0gKTR5bVRBP3F3zTbRMCYsqvnI3VITBZjHvo/ScZFaoAAMmR1qCYiBv8S1twhbQSa7mIeqC1L70yC2EBEfTb8Hst+EoCN63jSSvqnvesOwDF1/D8XHcCsXIUx/GK92SNZOeZMb5KQG6j6DeEN2mSutjWIOcQj2oeXtVYsGuIwhqK7DriRWoMXnouD4kAFRFfQIpH7H3Qy70OJTrljQm4Ukr6w622w00NwD7g9/unu/is8hqTeN3vNrzhUGBoecaJAEAtRrHuP6muow0TAmJBr2oD3/6QZcVUhdh6TeMN5mDSZxBeR/Ct6sIdlArZC8HM9LoZmPoNm7nfghQOgK2mp+t2826cWXENZ+FgoPAwkk9YbBjf5yP44qvac6N1ZYhOzXCRPn9WVgAagWgDJQiv4fgj8Lgu24Ab+M+FNe86VXncrrz3bvV/HJKJAeCa2WXJ1JbAGSuCgaSP8DgiMuFTfY5zr31n2yr3WKyzZ7HorPuOdIXIokLj4Bs/NI/MF9dDrKm16Vd0QJFElcEWToXJvFZ8a2vqZKTDSMiUl5S5RtM8sFkwu/QpNXT6hluyQvR8tboPxy5EoS52bxZyFJNyMVrxEyf+jqK8Kj4E0Cb9qwAVfCA2jx14APifP7XVXQ3xqkN+7hJSBQKDwBA0RD4udC5qMgdSO6p6TmPWjufjezTb0TYmdWfc1a3oPm7oawA01egyTfUpF4uErwG1B/MhQedasqwV1v8iok9WZEEq4DbnA4imWUgAzoQVcBn/otZ0PhIcj/yg2wCOR+gIZHkPQ7qr6e45K8zvXSCrtdx94T0rZEoyaTnS6hIqpfmciYaBgTE4nRn6VTAhJMtB+TSAIyH3FZUMXfAKGrjYgvG1z0JhJ1Yj12UFc1C6WNgI9SGnylknaZWIMfMTgAjwtUE192bHu9eiTzwUovbwQbFc1+y4m4NEP+QZcSG19c0eNFPCR5BZq4BMI2IIjiIgPrPNpx+1vshPJWl6LrT3dCR1QTU3ii380GoCkoPoWm3jiqgWQvcSYa+1MI253Qj9Dm/XURW+AmB6VNLlYlrRBfCIn3je7rjDK2R7gxMYkthfh5boau3ZC+pa+99kRCJN4ftJYUMqRKuvLnSYC/wLlphopjzW8DRZeBFKpbsUgCUm8dnYuomCB67fpI1D332VSJSMy9T0MKIQHEnwuUobTHCUXplahgcIk7QfNRp9zYwAfhJhi513phx7bVa0JiC0dfMACRFJK5NepXVXLpy8nrkMTyUX+t0cRWGsaERCQGNe93y3ZJDhtcRgvXC2kPUAR/dtUDvmoR7b7d2aniitjqPl19lk1sCdTc7GbP/uDgtJe8gjDzcVdZHh5yIlX7CbzY2G4cJBJDExdHsQTPJQLE5o3ui8QWuTTe/ONA1tW9eG9AEhdERtRFyQUdIJELLjzq/pbhGWUTHfFnQsOX0GA3eE14o5yddSIw0TAmLCLiqqlPIJr/pavGRlyL7sxHqxOOsB3CTpcNBRDsd66XKn/8IvHjBvq9zE2E6d8G8kAKzxufVZek3wXxxWiYReJLqt9i9dWeXzzUa4bYYtCDzg3mNfR9JiICNe+Oso729RqF1FS3ElUto8VnobgSiEPyCiR+3rhk6InIa8piGy/GVDRE5GvA9cAhVT07uq8J+B4wD9gJvEdV28V9ev8f8HYgC3xEVVePpb3GiUMxQ1oYAAAgAElEQVS16HzWmgVvSjTLH9sfrGoOCo9F/nEfyjuhvB3iSyt/Ei9qERK2Ab5z2wzdIKkSW8IetLTBBfrjZw3b3zssvAjd/+JqHWJLCev+dMxXGhC1Momf+7qiSxpmXaIDJeeOG/Z+eRCfC3JxFOMYkjTgz4S6z7rPCnXPUeVKVHMPuJoVacK1brkLTXcPa91iDGesVxrfAP4N+NaA+z4HPKyqXxKRz0W3/xx4G7A4+ncJ8B/R/8ZJgKo6X7TEhgUnw9JWyH7HCYbLZXRujpoPjnrx1PHx3D8tgEY1FFVW/YqkIPNR1z9KAyT1lqiOoXJUC2jP7S69FJyLJvPRvkwxDfZC1xfcioZaKK6Fzv+NTvqnYe+Xhl0g8RPmzgMIi2sh3I8krkK847QGGQENDkTuvB5cMD+Gpm/BS5zbd44kr0RL6yHcBZJBUteN8ExxtLwXCJEqmxpq2AnF56NU6d7dA5OQfxhNXDahMvQmImMqGqr6hIjMG3L3jcC10d/fBB7DicaNwLdUVYFnRWSSiExX1f1jY+3JiRusO3A/yEnjEjxWDaOZ3LOAh6Zvwot2btOwHbLfADL9FdOqEOx2lbGZW8dsxSGSRGPnQO7rLjspcSHqzat6Fi3+dCTze6/dkGB/lF48270X5R3Rtq4tAGjh2UjYCkCnC7qHHWhpE5LsD5pqeTvac4cLVNf+cdUDeiVo2BkJfgGNakqGnaMlZ79khota7kdA0N+4UPOQuw+Nn9G3uhK/GY2fDflfQvKsEV03WlwDXf8AKOrVIcnLhp1z7IvonazIgL9ToIdx9S0mGsdjIsQ0pvYKgaruF5HeiqOZwO4B5+2J7hsmGiJyG3AbwJw5J49vcLTR8i73owz2uhmUTEJTN+Aljp2GeUIIXnFL/95c+9wP0MRZiKRcaqqWwR+QjSICTHUui/Bgf3zgBONcZC9B4lrciuMIEu4Eb4zbV0gGl/1TAKKK6YGrM+1yLrTwQJQ55IPfHA14A04rH4agFaQnOjb6ooGkXOpwbw3NEMLiJsjfC2HejcmJK6O2GB6qZSeIA/tJScrFhYJDEJs94GLawItB0HYMO/wBBZVVDvJes3ts8dfRe457vxOX41K7jeMxEUTjWIw04dORTlTV24HbAZYvXz7iOac6bq/irwLJ/v0Kwm5XOcyteIkq/PSv25gSIE64NA4EUW4/kaCNkEsvAnguK2aMRAMt07cLnviuCnm0q34rQPwWNH0z5H/s3GPp9w+eocfOAW8deEvcBkaxs9wsPr6w/1K06JokFlcDCbSwGtKVFd5VZaskoPYTQGmY21HDDlcMJ3XgT3ICV3gE9aYiyYsA38WAyNEnaBoC6raxHfg66Xeh/nzkGPEliZ+H1v0vIHwNKaox90+7ou8nQCd4qYnXqmYCMhFE42Cv20lEpgOHovv3AAOmHswC9o25dScJWnjM+eX9AWmHXi2EIRR+ES3/x+gHEZsHsTlR6wyFxBX9g6DfAuUNwx+jimulMHYxDfFq0ORVrlgMce6hKju/jhZecgVh/EL3tzd45iyJ89BgK5TvdLNvPQip9w6asWvP16DwU5wyF6H7n1B/MpK8cFTt7E9gyKH+3P5Nk8AFprUMXk20IvJc9lvpBUhe5DZjSr0Nst8FyeMG7g5IXIkMacAoXtNxs8lcN90qXFIDCVtdKm/iTcBR3ASnAco7UC2+pjqb04mJIBoPAB8GvhT9f/+A+z8pIvfgAuBHLZ5xHEobR87akTrnM9csI23gcyJwldL/A8qvRHUHc/uPxS9A8485t8DADCE9ElVNj3HtQeodED/HDSKxueM2YISFp10fK3zC9M2DA8MSQ2reS0gtFJ+A1HvxUv1ioEEbFNc4V49mce4agfzP4DWIhgump4bv2x22o93/BeHhXsvQ9Lvw+vokRa9b3g/BepcV583qr9wGvMQFqGTQ4tMunhH/LSQxusL26kSiLAno9YZrOSoSrH5ipWE3SOK0EZuxTrm9Gxf0niwie4C/wYnFvSJyK7ALeHd0+s9w6bZbcSm3ryPSeBogCVwQb+hHqriZ1Oh91BpmXRO5YD/485DE2cN+MCKJEdtLiD8lcsXc56qb8Z3dXmPUxG9s3QMiUX3G60TDDtxKqbHqa9DgoNtC1Wtxz5G7B40tGJ5JpkfccY4Oub8bwlw0mEc+eo1DcLDqxoJh8SXI3tVXQDhwDwnN/8oFuHuD8l4L5O9H48tcxlhsofsell6K6le6IJaB+HsGvYbElyDxJRXbNBIatqOFpwFFkpePkLZ7HLwmt6IMdgJTAHXxouSVw4TyVe0ob0W77wS/ySUfnAabRo119tSxmqoM6zccZU194sRadAqRuMT5tIfO1LVtxLz/14qG3VEX0jZcK+dn0NIiyPx+xT84L3kRGl8QpVV2urbn8TNPypmaht1o9l7XtLAvdfiW6oreettfSMK56TSI7hsiGsErQDFqoz3g4VLnXFberEhY4rjPpjhIMDRode3Jw8MQW4okLhj+nge73PFeYRg42ShtdAV1YXsUA9rnrjfY77ZslRrXdE+zUbwomhD4I+w58jpQLaDdXwV14qmltVD3JxX3nXIFgu9zzRtL6wFxLtQhqb0aHkELz7tWNrElSOKiYanMGrS6zypoc2nEJhrGyYIkLkNL66JA8yQXhA47wKs5Rp77a0OLK90PpC9lUqG81aV/Js6p3F6vcUIUUmlwCM3/xG2ClHzjoFbjFT0+9yOX9eVNd3cEe6PU4Y9VPsPvbWYY7MEJz9IRXY1S82G0vHmYO0e0E/XnQRBtciRe9H+6b6Xh6iO+gtsZLwmll9DSS5D5vb60bA2zbhDVEkgeLa0f0tm1wdmogET5JmFHfxA72Olckv4S8FpdfEpiLpMufUNl70UlhEdwXWF73/MD7js5MPvq1ZAa164kbAcSrgJ9wM6CGh5Bu/6N3gp8ShvR0m8gc9ugyZEkLnQt6b3mYasd1RDKW1wbd+2O2r+vqG5VNAEx0ThFEK8WMh9Diy+4/Zi1DKlrkMSlw4KMr4tg1+DYSO9+zuEBoHLRGEtUwxHrVVQDF0AOoxli9i7U/xQyJHtLw24ob3SuuKh2wj0+7wZZb+qA9M8WV1mu7VG18avjMpJug9JmN+DHlg4rMFMto8EBCNvc7HagG8ybBF4jkIHyi0Ac4kvAb+47xyVKaH9mmk5yq6NgZ3/wv7zJ9bZKXOhiPPkfo4kVTnQ0cCug8AhQdkkXKEg9qq7FogYHo0pv3PuprVAuQXFq1aKhYZezx58/ONgOrg6FeDTgi1v1jLSTYXl3X68uGdJhWPM/g8LjboJFCNmvo+mb+jY/0sJTQB683verwQlieSvE+1vKiySR1LXDX1tDN6EoPuMEigSUd7nnzXz0pGobMhQTjVMI8WqQ1DWQuuaY56gGbmUQHHQDYGxxdXsf+3OiJf2k3ifExSTGKE22ClTLaPZ7bi8Obw5S90m3xWrfCblopjzdDfpBj3PNDBWN3ANQfM650eo/O+BINGhrPhrAlL49HqpsIC2SdvtojHQdwT6051tQeNK5frwWNPUGqHm/a3fuNaKJyyD/E/qC0ZqD5Nv7n6S8b3A/rF7BCTsGvJKH6zC7A7zkIFeLljZAsAmkOXILBUCNW0lkf4DWfcK5ZzQbiSi4vc5bGdoJV8N2KG9DtewGT2/6sFWZ5n7o0odjc5G6Tw9+r7wMZG51Az8hknrbsF0Kw+J6yPY2nvDQzK148UXR63dHdUQz6dtFUFPue5K42E0wgn0MqnMRVwyowRGGemHDsBtI4HkDXH3lbU4wvJn0VZ1TB+FRNPc9qP1Mlb2ySqClE1KwWS0mGqcRqiW05zsuUEmIIhA/AzIfqTieIInlaOmF6EeVAPJu2V1Nv6ZK7S3vdi4BcRW/1cZltLgWcg+4gKwcRLP3IHWf6j9BakBmuoaFWoD42S4APBRvkssAGhKnEEmi/mzI/SDy4eMG0eSbRm11p2EW7b4jsqMlaoY4NXKD3QWZP3Tpp+kbXGwjezdII9Teihcf0F4jvmjArBf69ucYKKLxZaA+lJ4HEtDwxf7BvPR8lOHWiAseh4DvBKG8OaoAr3N1GHoEgnyUnZTue99U1a14cvdHLqYA9SZB4jLIvGfwd9Brit7zkVdrEpuD1H7s2G9c8SnnHvMa3ESg+Kx7D6BfxAat5pJRIkHJ/R1bFPW2ilrCqAKKxKZFNwP3/eq53a2uxCdMvg3JvBvxZ6Kl1VH9zxBh8BqiuND+ijMFXQznK84FV3srElv46g86gZhonEZocZ3bOKe37w8CwX40di6Sqmx7SecG+zhaeM5tHRpfhiSWV5118qq2BgddsaIqUESDV5DMh6t8ks4ouNwJTBoyq8ZVKacug/x3cQHbWSP6myV1HSQucJXEA59e1a0wNMAl+CloDWgnqqWq3hPVPJr7qUvdTL2tb/WnpfX9s3evwdkpNcBk5y4JdkNsTtSe5a6oBsaHbANa/xd9g74kr3aDXOF5oODcMunrB9V6iCTQ+MVQWukG+sTZ/QaG3U4YFdB97lqlxrkqJQDySGwWGlsApV1AN+A511dvDKa8GbLfiyYckRgFnVDodjUl6f7Ym6TeDonlw97zivEmQbADtD7K9BpYv9SEaxuSHSCi7a5OJ6oIl8QlUYbgXvpWYImLwJ/vBCP3fcg/Eu1h3wKUoPBLNNyH1nwwEqZjfP4i9FWiV4JmXQW+FtBgv4mGMTaoKuTudT5er9nNsjRwM9fc3WjykooCt6qKFp+C4qNuAAl2ovhIcpR7SQZ73AohbHc+7OJ6tKY8zJWmQVuUDbRoWBxA4meiaDSjzLoZ7VDii1wGUNgByctHNEXEG3kFoj3R+9kAMh16NwLS7qiyvWX4Y46BltZG7pQYGlvcv3IL9wFx5+4IXnEiWF4PMc8NPmE7MAdy349iImUgcM330jcgUb2HeJPQ2OxoIE27FVH8rOGfud/kXJBe8+CKhdgSkGch3AakcNX73eB57vPxJgMJSL4Rwh/i2oA0QWw+Er3vmn/cvV8Sd48nANJu1VF4PNp5r7cFuj/ye14hkrrOxX6CXRBbiCSv7T8mCTT9Huj5dyjvjuJIi5Ga3+4XWa8Waj+BljZBeBjxZ7vnEY+w8IJrqe61ALtBD9CXseY1Qu5uSFwFugUY0tpfA/e/V/n+7OI1ojXvh7B1QmzQZKJxiqGac4FYNJo5R8vrcL/7wZLqX5aLj1uWd0Q/rgrqFcob3f7M3ky3Z7UWIfdDNDZ7ULCxr/21xCF2RvWdQ70mt1d0eAhkvxuMGBoczqPd/wbaBenfQZJXDDou/lQ080nIfdO13ki+efjLeJMIG78JlPGq9RdLKpr9AxSht2OvpKveT4PiJjeA4bn+TL2iIZOAEujhyN0RB0LQDpAGkBpXI1LaELlictFAnnEp2AOKBCnvgNgy9xzBfrdK6XXZ9F2T7yYDvW1geu9OXoIWHnWrSy1GPv7ADZKpt/a5DjX51kjIUq43Vc0H+v3w4X73WGogjDLF/GnutbTH/avQTRqGIRQedO9N8u3D9hcRrx6p+4SLm4wQs5PYVFQiG/s+s8EiL5JEEucNuk9VowB6UxTzEZc2LgLxC9z7HvZWmddEbrvGaHVRdu9B8pqquzkPLPYcb0w0TiHCwrMuGNrnXwdNvgFJvgUt73I/cK8n8vEnQEvgpcBvQcs7kApEQ4u/cT8M7V1ix0E8tLS5TzTC8Ah0/IXzCYsPiSvQus8Pa49xPCQ2H818EHq+DrFpUPPREVZC4lxPQVv/NQ8lfhaE10Ns6TE3LnIBzOMPVhr2gNQMskEkhqbe4V4/PAiEbnacum5QzYBqgJa2utWTPwuJD14VhcEBt1Ig5q6p5+uEyavwvFokcQ5a+KXzz4cH3GtoVMTp1UFsflS3kYwG+U4IfZd+Gg4p7vPmuIFW1bX6GGnP8uBwtLopRVln0bV6TVD7R2hYhNIad6c/2aXsDpjFU3oRSqvd62s75H8Emd+PXr8FNyOPepOh9PWekjRVdSwoPg5H/1/32IYYpEdOKz9mkkd4JFptRUWG4X73u/BfxR2muWgVFb13yctctqLUuYkJRMKxH6m9Dc1+P0qljkQ4+QZkzLfpHV1MNE4RtPSyC8h6U6E3i0MDyD+ISj0icRQfEisi108H+A1uphW2MSwl5FhIyu3fHD7ssoakFvylkHKPV1XoioKDXpMboAqPOr92+u2v8uRDX+qtkLwY19JihMKtXh87cUZqNKhahI7/6Xz0UkPYdDdefN6Qc3IuPqN5V+w2QiFaWHjSBdQTFyE1twy2MXExeE2uaI4ASayAWH9KpmoJbf9LKD6Eq9ZOoom3QOMX+mMe5a3OpSUJ3My1za06EmciXpNzpWTvdp1jNedcQV4zUvMhJ1xeC9ANYRbn9hEI94J/UX/KbdgFpSgOpSGEaSisRGNLhohxtEqRJEI4+Fpjs6Hxy64eSLsgfjaeN9T9chhIuO8JTf276wEkr4Hii078vElE/k03mUleVXEyhmrJraLodHfkHxnk2uo/rxi9r3XD40veFCDpYgUSOpdtJfugiBfFddStHryGaBU8kChJQOpdQD3Y5T6b2EKXQjyK3Rl60eCwcxvHlvVliZ0oTDROEbTwmBvAB/5wxHezu8IjaOYPoHfToYFN+SIfq8QqbOvgz4BgXRSgTrrBQ1/qzwQJ26KBKRe5W3A2FZ5CU28bXKEcdrkftdc8wg++hGbvdum9EkfT7xteeCcJiM2CID5i1bEWo1Yn+Lhc/O9Dw58NeA11vZQKT7tFS/4haPir4ZlP5W1Aub8GYaAJIqjfHM2Sy+A1Db7G7ANQ/Lk7hgI5KP4MzV6MZG6K3tOZuNbsOXeON2XQ9XiJ89HYHDT7EyivdbPV5LUu9RTnf9fEtVB4AReQF9AUpK7vt6PwhKvJ8Oe770XYCYVfQfpNg1OMNRu5V3y3ShnheuU4rhKJLUF5KCo0LA4aUCV+Fpr5Hcj+IPpuBC5VO35tVbNvLa6NVjvR8FVeixZX99VYAK76vecOtxL1mlxtxIDsN/HqofZjrm5CEkjyqooSF0RSaGxeJDaNLq5TfMYJROLiyA2VBf+MaEva3dFELu5syX6NUG/p219mtND8L93kqPg8Wv+/T2g7nvHZaNgYfYLd7os7FElD2OXaH6Te6lwPYYebmYdH3e3ktYOK1o7/OnvcUpw8rgdSyc0Ug71Ab0xlP33phuKBJqI+P2F0TkCYewDt+ju0+/+inV8kLA7pfFveBKV1zg0gdZC711XYDrw0iSO1n0TqP483UjW6Zl1KcWKF2zND8oMPh11uxqpZ52orrXP1CAPP0RBkspude7Pc7HXQ8aLbia70AhR/g3bf7uoAesn/DHoz1ZzV7nb+532neLH5kPkTJ/DedKj7Szx/cBaXeE0QbItWCQf6BKOP+PkuoC8tIFMhvhQZuB1s+WU3yJHvdwkRH7wSABcb0cPucw4GZ5v1XXPQ5nouDfk8AOfiTL8rGjiXIanf6j8mEolWBmIzXSNLvw7icypfZQT7IHdP5KJLu38aQO77zgXbe17+ly5G4k2HsB3NPzrCk+WcCy1sp5psJkm+0U12tASlTe67H2wGPdJfIS+4FYY/001uelclXosrmhzyPXrdxBYCMYidecL7t5lonCpIg3MXDUVLzncrCST5BiRzK/hT+mb41HyoujYjWgRSlMop8vkaykGiPz7iDAGJXA7+XPDngV+Dm2lHrpLiateOPOiG0lYIC5D7TtT0r/d1Ano6lZfXdLNrcyn6kQ3eKiUMDtO+4984vPUfyB151LnGBr4l8bOc4EgIZCE5tNV2CETvD737fgwRheIq55cv74TCo2ju50Oeot3N2r1pbnWgObfa6jOidzHfO1CHQ+6P8Ce7mah2jbxqUmXdC3N48HsFdmweHosol4o8/+g0vv5/LuTufz+fLevSbtOjXrypLqVUaoF8lCHVNMglo+WdbvAj5j6q/A+G2xFm0e6voN3/4d6bkSjvBLzouQZfA/kfu4Ezfp4L0vuLoPjIYKE9Dpp/GEhD/MLoe+1FAehatPDQgDML9K1E1B/+uYZH3EqkvBdKW9CeOyseyCW+BNI3RplzUSYaGbfqEHG/sfLGkWM0knICNVSsXyeSOBfSN0HyxMdLzD11EnHkQDtP3vcsO17axeSZzVx10yXMXRb120leCbn7QGvoi16qui928sr+mVz8TIgtpZgvkkglqp6VSOICOvbexbYXM8TiQhCEnLHcI9Posn1EYqi/kN88vo8nf1wgmVbe/qEaZp0xoG1CaSXbN8QI8+sJSgGFIsw5cw6N6e19Of09PbP4zj8V6Wjdiqpy+Y1Xcc37BgfSd636Egd2bCDXHWPKrPXMWzGZTFP/ikP8yWj8XEqdO/GTdXjxwWnB4tWhiYvdftFadumhA1pEAC7NNTwKlKMss+2Dj3sNQIy2nb8kKIdMmXfO4FqP9E2ExV+jQRitMRTxFS9906Cn2bLqEcpH86BCzbQnmX9Rv7uwVCxxx+e+wzMPrAFP8OTn/M6f+NzwB/2bLP38G7vY+JQyqamLXGfID786hRtiuzj7iuhzSV1DWHqJ7Run0dXhM3tRieZZzsfeR3gI/BmEGsPzJrk9y0dswdIrzsNXGkAUN9sJ8QuGZM0FELQS6jSO7D9MUA5pmjaJeAwnvgMyilSVoBzgx/z+uIyGrg7Fmwo6oOeVl3SrqNLLffUxknwjWr7TBbglPrzPWRh1DO51WVUaCKf3Ja9EY4tcL7bYWS6OGL8AiZ+NeJmRd4s7gWju51B80nULqPv8CV1tmGicJOR68tzzpR9RyBVpmFzP0dZO7v2nB/jAX93M9AVTXaV2eZvLXqE3D77gBsLU4FTTJ3/4HE/c9wyX3bCcN/3uVdUZElvKmqfPYcqUZ/B9pZD3eGnVFVw6N8qp96ZycP8MHvx+D01TE5QKyn/fXuRj/3wZyWjw2b2lyH3/2sak5qkka7K0t2Woqe3g9/5OSUbatmN9K2ufTtJ5OEcsESeba+XK9wT4vhuEwqDMvi1r2P1ySBiClouE8TWc88Z+0Wjbd4T7/mEdu9Z3UVOv3PDHmzn36v7aBBHf5b+X1gN5SL5teCA8tgj1mihmy8RTDXixwZXvIim2bb2I2/90DeWyx0f+dhnnvmmAmzD5Zg63nkFDw3q6OzxqJ4V0HD6TKVP6Gzu3H+zgB1/pYdbsRsoloe3IQf7o33Kka13wf8MzL7P64bX4CY9cZ550XZpHvvsky99yLjMWTuPIgXZeXrmTaYuvQLQT8InVJnjqR8/3i4Y/k2ceuYYn73sQT3Ikapr5wN/cQEvtgCwuprJvaxete8qkMq3MOGMZkxqHprLWQO0n3aDtj7xhlRdfBPHPj3DE1V7sWLOOAzvzIEKmPs7ZV0whPkBo927dz8N3PcmBnYdonDqJa2+5nMUXLIC+9iyhE2t/Bi4G1BjF2KJ9v3HZd9R92mWD+S3D41TeFCDhtpmVcNiqqxLEn4akr3desqHEznOuPoZ0O9Y8SHLkzLXXg9TgkhhO/CZmJhonCdtffIWeo1mmznWxh7qmWkqFEmseWedEQ2JQ8z4ILnXdSzVwBWKxJYOyNV5etY17//F+juxrZ+/mfUxfMJVll1a+t4GIsHHNGdz3VDd1jUWOtiV58wcXDDjukS29A8//LxLJAvGkcmjfZEp6Lb1NQFY9Vkf7oTzbXorjxxpRLTF9nrBzc4ozVrhznvrv59i1aR/ieUCOo4c3cXh/O1NmueZ1ocLap2IsWNZDT1eMfE7Z8EKOc6K4ayFX4N5/uJ+XV5Vp3d2AH0/zs/96mEx9hkUX9M+uxZ+JJi4A7UKSg3PyASR+Hs8+eiG71z1E3bS5vO0P3jLoeD5b4BffamXtM2lQ+MnX2lm4vIdMg3NNeJ7H80/czOFXAl7ZWGbumXGa59/EDef2D8aH97eza2M7QbaGIBQO7j1IV3tPn2hsWb2dTF0NW1ZvJwhCst15Js9sYu+W/cxYOI1sVx5QOg52cWjXYeLJGJNnN5PvLgxKuV39yG6mzL2AeDLOwZ2tbF97gJZZ/YPXtnVlHr9nLstWdHHwQIynHqrho38/fD8O10BwSBPBAWxetZXVD61j9hkzuOTtFxJPxPu+O9nSW+luf5zJM2JoCOVSJ21tNzBjsnu/Og93ce8/PkA8GWfq3BZyXXl+9K8/5wP/z81Mnz8VjV8UZcNNc5tn9aIHIXFe33c9DEPWPr6PvVv2M2dZmbOvaBicLu3VQ+0foIUngQSSunZUuxpI4iy0OMfFNbwpuAy/Tvcv/d5R3wZAUm9xbWD8lhMe0zDRGEMKuQKHdrWRaaihaVoV+y0AhWxhmM8+nozT3ZHtuy3iuarVY7QZaN1zmPu/8gviyRiKkqhJ8JP/fJDGKQ1MX+Bm2KrK9rWvsO7JjYgnnHv1MuadNbvvi7hr016O7O/Aj9fT0VoiXZti24uv0H6wg8apbjY3feFialsu4sC+dsJQWXzhYjIN/TO9nq46Oo7UU1PXje+H9HTF6OqcSqngBtKO1qPs2riXeCpBoSePiJCalOTXP3iW3/nU9dG1Cs89uoBnfnUAUJAEt3yuP9Vw18a9dB3pJtedp/2gc5P5MZ9VD77YJxpBELBr42E2PH0+xVyehRcUWLK8QKqmv8dVEATc8dcbObAzRjqzm2t+t0imvv9n8/B3nqBtzxGapjURhiH57gI//a+HePdn3tn3ni25+GK+fMdKct097N9by598dcWgz8XzhPbWMq9sdMViLbMG15w0NNcxbV4Luzfvo6czS8PkOpqnN1JT74rmMg017Fi3m672brqOdCOekGms4ZzLlw4SjcYpDax9YgP5ngKTptRT1zjY517IFjlyuIVtm84iKAd0HmmvehOnVzbs5vbPfJsDOw+RziTJHs3y1g/3x5LimcU89dDlhNMWcBUAACAASURBVLm1xOIBhdIS3vdX/a6jLau3UyqUaN1zmB0v7WLGgqlMXzCVl57cyPT5U5HUtQTF9XQdfJmX15QIQlh6YYz6yS34yX5BX/XgWh6+6wlq6tKse3IjGirnXr1skK3iz0Bq3lvxtVWD273y99HCExS7HqeY6ybTuAhJ34yXOPPVn6Dq1/PdFstjgInGGNHTmeW7X/whRw8dRYG33fqmPtdBJcw6YwYiQrlUJhaPoap0tXdz1c2V9YwC2PzCVkrFMl2HuynmSnQe7mbavDIbnn25TzRe+MUaHrrrScLABW43PL2Z637/jVwQuX3WP7WJuqZammc2kj2apa6pjq4j3Wxds4MV110AQE1dmg/89c1sWbWdRCrOkhWLBg08Z166mKcfeIHDB5RyuUwylWTy7DpmLnYuriP7O6hrrKWuKUMhW8CPecw7cxZ7thzoew7f97nhY2/nW397H0GpzOylM7j8Xf2DcSFX5JUNu2nb2065FKAUeXnVNuqbnR88KAf87I6H2fDMZlI1STzfZ8uaR3nuZ6t572dvpL7JnffT2x/iaNvRvsfc8bm7+NS/3wZAMV9k47P/f3vnHR7VdSb835k+oxn1giTUACFELwIMGIwpxg0T19iJ4yROnNhxNnWz2c1uNsmmbJJN1uvky5fmeJ04dlyCWzAuGFwAm94FAiFQL6M6Gk2fe8/3xx2NNIywhWNb8sf9PY8emHvv3HnvnbnnPW89tWQVZJLW2IWqqGTkZ9BwvBlvz0D8syoWTuHeX9zFwdeOMW/lTCoWJubRZ+Zn4MpIoae1d+h15pCbYe6qWRzZfoJLb1iEEBCNqKSkO5g0RyvG3PnMbowmA57OfoL+EAgwmo30uj3UHjhLRZU2iSibVcxT928iGlGZ4MuhcGpim46SGRNxpjtor3cjpWTJdQtHLIh0N3Xh6exn0uwSjKZz4kw1LfR19jPQ5yMcCnNq/5kEpWGxmllx89Xcf08LkXCUG758KRNKh1pqhIIRet19VO88SSQYob/Li8liIhTUEi0iYSebHpyEr6eN47u1zsJ1i7KxpZex/l4ntljxed3Bs6RmuXCmpyAMBuoO1ycpjfcbYXCgmNbwv//ZRn+Ph8tvW8GiK997hfFBoyuNC0BVVS1P/V2Yf6f21dHT1kt+WR6hQJjXHts5otJoONFMf5eXykvKMZmHvp7comxW3raM1x9/EwCpqMy8dBozllYkvf+lh14lGoqy8qNLmb5kaH9wIMjpg2eRiorNaUWqKqcPnmXmcu2HHA6G2fyHrdQdqifQHwAE9lQbqqIya3klJrMJVVHxdPVz9kgDQX+IlDQHJdMnJllBrgwn89eMnM8/Z+UMLr1+EY/+6CmiYYXM/HRu/Nr6uKWSmu0i6A8RDUWx2rVgfWdrD3NWJabVXv+la7C7HDQcb+LGL19DWtaQT9poMuLz+PH1+5GqJBqKEugPxOU8sbuW6jdPkl+WG/8+07JddLV08+pjO9nwhSuRUvLqozsIDoRAQjgUYdemA9x7/5DijkYVzuyuxWAwYDQZObnnNMWVhUn3Y9bySioWTcFiTXaBqIrKgMcXf+3p6k94f87ELD72rRt4+U+vU3+kgbmrZrLyo8uwp9gIDATY+fQegv4QWQUZdLV0I4wGMvMz6GzqYfvGXXGlceT140xfUkF/t5fMCRnUHjhD1dqhduypmS7u+M4t1B9rxJnhpHRG8qJGgYEAj/zgr/g9Aa7+3Jr4ZGKQ3OIc7C4bZpsZq93KxKmJvntVVZESZiybRsAbICMvLZ6UATB5dgm+vgAWmxklomC1m+lt76NysbZ08L6XDlF7uBe7cx6tDUcAmDBlNqGWAXY/v5/Lbtb6hxWU59NwvBmD0YDP46dgSnLr/r5OD0/87DkcLjs3fW19goX5XqGqkl63B09nP/1d3vf8/GOBnnI7Cry9A/zt1y/x88/+ml996UH2vnxI631zARhNRgIDQRprmmlvcGMwJd/6rtYefvP1h3jw3x5l1/PJ6YwLr5jL+nvWMXlOCctvuoSrPrs6YaYX9Id4/KfP0Ha6g86Wbjbe/zw97b3x/VKCp7OfzuZuult66GzpprfDgxrVrqWlrp0jrx/H2z2AzxvA7/Xj7Rng4LajdLf2ANrDfuZwPe6mbvq7vbSfddN21s3kuWWMFrPFTOmsYqJhBVVRkaqkaNjgkpWfgSvLSZ/bQygQJujT3HpLNyQ2awv6Q+z62z5qdtdyYk9i4Z2/3080oqBElPg2b58f/4Dmzju49SipmU6EEChRhUhYcwll5mdQu+8Mfm+A+mONtNS1EQ5GiISiRIIRfH0+3vzbPgCsdivF0woZ6PMRCUUI+UIEfAEyJ2TErYxBNj/wCv+87vts/sPWpPtRu/8M/V1DKaedTd201rYlHJNflsfxN09Ss/c0zafaSMvWFKTP48fd2IXdaY8pMRVVUTEaBUazgbqDZ+PnMFlMTCjNpfKSqVhTrPGkguF0t/ay5U+vs/v5/SP+xtvOuqnZc5qT++o4uv1E0jFTF0xi5rIKbA4rWQUZrPnEioT9+185wgsPbMXhspNbnMOuTQfY/MDQPckryWHlR5dgdVhJzXJhd9qounIuk2aXIKVk/5YjZOSl0VTTisEgMBgNNNU0k56XxqFtx+LyLFm/gEXXzMeRaufSGxZRtTY5XtV2xk1nYxdNNS30tPUm7QctKL/9qV30d7+7AX/P5gMoEQWL1cLRHSfo7Ri59uXDhG5pvAOqqvLU/c/T1dxDTmEWkXCUrQ9vx2QyJs2y3o7M/HTcjV34PNqgNeXTpQn7pZRse+QNOuq7UCJRXntsJ7NXTI+7SQCaTrbw7K9exGAQnNxbB8Al1w4NpHWH6zm2vYZoJIJUNRfF4dequfxWzWfsbuwiEooQDkaQqkRVJEajCXdjJwB7XzhIyB9GiURRYopEVVSMZiN7XzrEtZ+7gpLpE3FmpNDZ3K2lRJpNTCjNISv/wmI0B146MriuDeFAmNr9deRM1NIdhRBaHMUgkKoEocVvCiYnzhZ9fQMcf+sUQV+QI28cZ8WNQ11sj+2sIRQIYzQZUBWJwSiQqkpbnRtPVz8+jx+T2cixHSc4uuMEqqJSNK1Qc7EJzb2158WDRIcpHQBhEOzcuJsVN2huwWs+t4Zdm/Zx9ohWWFYwZQI3fOWaxKpwKXny53/D3dBJb4eHq+5clbA/Eo6iRIc+R4kqKErygN1S24a3d4D66qEiNkXRvsdIOKpNACIKalSls6mHzPx0osPOW1xZyG+/8SeUiEJWQQaf/9kdSZ/RdLKFwECIxhMthPxhHK7hPbQkLzywlcpLpmI0Gmg93UFDdRNls4Z6lrWfddPV2oPBYCAaUajZXcuCtXNiq/9Jdv9tP9mF2kJViqIwoTSH2v1n6HV7yMjVWpJc8cnL2bFxt5ZaXpTF9f9wNUIIVFUl4AtiNBvp7/GSkZeOEIIBj59IIEw4GEGJKhgsBswWM5d/dNm5l5dA2axi5q+ejc1pjSeYDEdKyV//exMDvT763P2sv/vCayD2vniIwvJ8TGYT7WfdnD3aGLeoP6zolsY70FHfibuxi5yJWRiMBqx2CxkT0tiz+cAFnae93k3p9CKWXreQZRsW0dHQmbA/HAzTcLyFpRsWsuwji7HarbTVdSQcc+SNanrbe+lp78PX52fP5oPxfVJKXn/yLfo6++lt99DX6aHP7WHn03sIhzR/cFdbD1KVGE0Gze9tMiClSldbD0pUYd9LhxEGEgYsRVExGA289bf98aDo8hsvwWQ2IQwGbClWlt+Y3HJ8wOPjz99/kk2/24KiKEn7M/LTtMwoCVaHlZT0xKBs0dRCHKkOhMGAwWgkryQ5K2TLw28Q8odQoirHttfgbtKK6nrae2k93Y7BKDQrSoIaVVEUFbPZRPWbJymqKODojhMcerU6ZvFIGqqb2b5xF2arGVdGCsGBEAFvYsFkcCCIzzuUfJCWlcrd//0p7C4bVoeVT3//VnKLEjOLDm49iruhk3Aogruxk4NbjyZ8b3WHziYMzilpDmr2nE66Z9OXTGXilHxmXzbUTsWZZie7MAOfx6e5tGKKWFUUIsHIUB0PsPl3r5BdkEnJ9IlEglFef3xn0mfMunQaU6vKWHHTJQkygTaB8PUH8PZ4aa3rIBqNEhgYuj9+b4AnfvYsadlpLLmuitnLp/PKw9s5HbN2Bgd9VZUc3HaUg68cpb97ACEEIf9QRfa+lw8RCobJKshEINi+cRegZaLll+UR8odjFqIaV7aRUITswswEl24oEKKxpiX++z8Xm8PKVZ9dzeW3XpoUmwFt8lI8rQCTxUj+5OSCy9GQluPC1+dHVbTfnyN1pPzct0dKyY6nd/P0LzfT3zP2Li5dabwDkXAUcU4HHpPJGA/MDSKlpO1sB3WH6/F7A0nnMRqNtNd3ULPnNNVvncRoNiaY9iaLCWdGCgFvQJthS5kQDG053cYbT+7i1P4znNxTy/G3TlL9Zg0Htmp+3VAgTPX2EwgD2F02bCk2TBYTZ4820ufWArl2lxVVqtrsWUI0qrmHHC4HiqLS3dqDK8OZWHgtITXLhXuYkptaNZlgIIQSUQj6QpQvSHZNbf3zG2y8bxMPffsx6g7XJ+1fe8dKHGl2rHYLEyblJcVmpi+dSsWCSRiMAluKlevuWZfwYEejUbY8/DpBf4hIOELzqVaObT8BgKfLi38giMVmweqwYjAKTGYTdqcNn8dPR30n89fO5uzRpqTYQ2dzN6WzJmIym8iZmMm54SspIKtgyKo6c6SB53+7hWhEsxa2PPw6x3edSnjPtsd2IowCYdD+Xnvizfg+b88A7qZucoqH6hSKKwup3X8mYbAL+kPkl+WRlptKek5qXBGnpKWw8Kr5ZOZnIKVEVSVS1azD3JIclt+4eNg5wljtVixWCwajIOBLbJ0R8AX58w82svn3W3nkhxs5/Hp1wn6jyUjl4nJO7TtDU41miRRXTozvr69uIuQPY7Fq1mvA68eZ7uDQtmPa+41Gpswtpau1h2gkSjSq4O3xYnPaYtZHTM6BEEXTCimdWczUBZMSFNPSDQsJB8IUVRTibuqio6GTiVPzCQbCLN2wMGFi8dyvX+aR7/+Vlx8aoYXIKNnwxav44i/uZMF54nPvxPq712Fz2uhs6abqitmULxi5tuXt6OvsZ8fTuzm2o4aTI0wmPmh0pfEOTCjLxeKw4OvXZpdSSrrb+pKC2Pu2HObh7z3JU/c/z8Pfe4KBvqHAZmtdO68+thNvr4/GmmbcjZ10NHax9ZHt8UFLywZaSzSq4G7sZMn6qrg7Rokq/Ol7T9Le0EnQH8Ln8eP3BRnwaBlZXa09IMA/EECqklAgTDgYJhpRCAXDRMPa4FM4OR+paC4WrVOzQFVUCmKzKIvdgnmEQK3JYsRiH8orf/BfH9XOYdBmjw/9++MJx3u6+qnZXUvQF8LvDXBsRw2hQOIAlZWfwRfu+xRXfnYVX7jvk0kzPVeGk/lrZ+NMTyE928XCq+fF96mqyosPbqP1VLvmvpJauuiTP38Od2MnKal21KiK0WSMDaQqiqpisZmJRhTSc1PJLc5OUgigpb8OzrDDYQWLPTE4arVZ4t9Zy+k2Nt63iXAogtVuxeqwICX87f++xOlDQ7EENaoVJRpN2t/wOMvgxEEdZoypimYdyWGTisd/+gwvPLiNU/vq+Mt/PsWOp3bH9639xApyCjORUmJzWLBYLURCUeavnZ2gjNd9+jL6u710tfTgcNlZcWNi5l3doXoOvVpNT3sfzSfbeOGBrUlK9crPXM7KW5YybfEUPv39W3EOsxClKgkHw+x8Zi8Htx1jx9N76G7vTbA0V31sOXnF2aRlunCmOXC47Gy4d12ChTBv9SykKgl4A/i9QZasH3LBTp5TytV3rUZVVYxmA0azESWqsu5TK5lalZhqHglFUFWVcHBkS8PT1c+D//oof/nx00m/z0EMBgMpaSnvuvYhZ2IWd/3kdr7+wD2svWPliHGkdyI100lF1WRyi7IoGSE54YNGj2m8AxarmRu+dDXP/J8X6WjsAikpm13M0g1D6Z1SSnY+tZusgkzMFhNtZzqoO1TPnJUzUFWV53/3CgGvVm9QNLWAUCBMoD/AgVeOMHXBJEqmF3F81ylefuhVomEtY+itTfsY8PhY+4nLaDjexKl9dUTDCkpY0QbCqELIF6KzqZs9mw+w9o7LyCvJpbulF6lKJBKT0UBGXhp2l5aHaLFZsNjMRDzaQyQVidlhxuqwYraYKJ1exFubkgPwAz1+5l42M/7gdDR1xd0+SkSh9fRQ0LartYe//OgpgoEwNpcNq83Cyb2nGej1ccs3NmBzWGmubeOxHz/Nruf3E+gPcPCVo6y9YyUb7l0XL2hTVZWz1VrqaiQYoaulm6xYbcuZIw0c3HpUW5VvGOFQlM1/2MYd37mZsllFNJ9qJRpWkKo2AKuKSlpuKjOWaWtr2FKsBH3nDhaCksoiwsEwuzbtQwhwpNmJBCOYrGaE0ALXnS3dvPnsXvo6+2mv78Dn8SOl5OyRBgqm5LN94y4mzylFVVUsdjNBXxBV0b43q92ComiKJC07lfxJeRzdPtQo0T8QpLxqEtZhCuvg1qOEg2HUqErQF+bA1qPxTKGMvHTmrp7FkTeOYzQZMRgE0ajKZTcvTRiMb/zKeqZWTaGrpYcZS6aSW5zoxzcYDTjTHfR2mLCnWJMUJoDZbGblrcvoaumhsDwxxlRcWchAr49wOIzZbMJgMlB/rImbvjrUbTctO5X1X1hHU00rxmCYVbcvp6gica3sSMzCMhg1N2rQn/gdzVo+ndKZxTzxX8+hKgq3fGNDPDFgOBvuvZKW2jaKKkauvm453U5rXQcGk0G7ninJKwWqqmaZmy2mv6to7nxruYwGo8nI9V+65l2//71GVxqjYOLUAj7/s09w9kgjKekOCiZPOGcxHoEEGk80YzQZCAXC8ewod2MXfZ0eLSCrqvR3ezFbzQS8Qax2K8d21GCxWdj0m5e1wJ5BoCoKZpuFI6+fICXVgRJVUGN/Es0FIQyCSCSKwajloF9lXk1eSQ5HXq8mEtIygaQqcaTZ40VczowULHYTPs/QtZmtJtKyXAghmDSnhNefHHKdDBLyhyiv0szqjoZO1Ig65MKS4PcG8fYO4Mpw8upfdhCNRGmr68DX58cvAgR9IdrOdHD0jeNMW1zOX3/+HEe3H8fj1tZDaDrZyp7N+zFbTdz4FW2Aaahu4tTe06iKJBQM8/xvtzD1t5MRQnBw61E66js1F58yVAgXCYWpO3yWnvY+1n3qcl57/M2EALO318fS66rILcqmubYN6wgplsIg6GjoJBKO0n6mg+zCLJpOtqBGtcGjcMoEfJ4Ae188xJE3jtNS24q7qYtIUJOjvcEdy2BSCAfDNJ5oIeANkZqdykDvAM5MJ/7+AGcON1A+fxJCCGZcOo3Hf/JMvBGuu74rKV3Z5rTj92gpwwaTAdc5MaBZl07T0qHd/WAQTJpVTG5Rch8lg1HQ5/aMeO0Go0HLAvOHUKMqOYWZBAaCCbENn8fHH771KN6eAcLBMMtvGLJWXBlOlt94CU3/2Yo0alZb2YwiKs/pOGBzWOls7sbn9Y+Ygnx0+wnsKTYy8tKJRqLs33IkqWuBK8PJrd/cgKpKzaU6AimpDqYuOP962mWzipmzcgYOly2hVgS09Oq9Lxxk/5YjhPwh0nO1OM2MpRXve8X1eEd3T42CzuZuHv7ekzz202d56N8f5+U/vkYkPGTyHnjlCO7GTmr21HLkjRO0nXXz5rN76O/xEg5GEMKAI81Bf5eXjsYuWk6340x3YLIY8XsD7N9yGIvVjKern12b9rHr+QOc2nuarIJ09m85jMlijrsJ4q4LRWIQmoKxu2yc2leHt8ebGMSOqhgMRva9dAiA9JxUvD2+hGvz9flJy05FSkn9saYR0yyj0ShnjzQAcOT16nhm1SDhQJjag2fw9fupO1xPa11HvNZASknjiRb6uwc49Fo1J3adorutj67mnvj7pSpprm3n1L46umOpj95eH56ufhRFIRpRaG/oihUcQlNNC/6BYMKDbrJps/a2026CA0F2PrsXW4qV4eEou9PKse019Hb0sffFAyMOWKmZTnY+vZuG6ibNYlPUeAtwKSWRSBSj0Uh9dSO97X14e33xZZ+1a9EG1s7mHoRBcPZoI0JAbnEWKWkp5BZnA5L6Y8MyoCIKdpcdk9mEyWzClmIjEhzquNpYE2s7H9PUQgg6mroSgqJ9nf0YjAbtGCmRkqSYRSgY5hdfeICN/72JJ372bMK+42+d5NlfvoAjLQVbihVHqo2mU6089pNnElw3oWCEzqYu+jr64mnYw5m2eAp2l017PgTMXF6ZNMuu3a/FRDqbutnzwsGkczgzUmisaWb/lsOc3FdHWrYr6Zie9l4e+OdHeOBfHqGrpTtp/2iwp9hYf/cVrP74igT3qKIoPPPLF9jx9G4cLjt5JTkoUYVNv9nCW7F06/cSVVVprWvH5/G988HjAF1pvAPRSJQ/fudxdm3az9mj9Zw5XM9z//dFdj69B4C2sx1s+s3LuOu7YgVeBkL+EMd21rD596+QVZBB0B/k1N7TGK1mBFqMoNftoeF4EyUzimg748busnHk9Wp62vroc3s4fageb/cASlQlf1IuUsJAry8hSB0KRvD1+Zm3aha7Nx8AZLzmAgAJkWCYPS8eIuAL8r//9hjRcGImkxJVeeg7j+PtHeDMkXrM1mTj02wxc3JvHVJKAgNBwoHEFtLBgSBBXxglquBu6MTT2R/LtIot2gN01LtxN3TSdtZNf1c/0XMyqlRFwd8fwNOpWR/BQIiQPxxLDVYZ6PVqcRRiKaoRBXfT0GChhBQ8nV6ikSg9HX3U7K4lHIrE3wNgMBjpbO7m2M4a2s92YjAZsDqH9QAygN1pIxKMYraaiUZVutt7h5SChN52D5FwmNRMFxa7hWgkmvgUCU2x2xwWLaU5lq7ceroDAbTWtrP35cMYzUODVOXicrJjMQkEFE3LZ+K0IZfN4derGegdwGDUrsVoNtLT2suZw5oiVxSFzb/fStAfjsdNOlu62Pn0boZjMAitgE0Qb0EC2m9826M7yJyQjsNpw2AwIgxGcouz6WrupmZYDUxqppPlNy5m5vJK5q9Jrn1orevAYNCSPGRsMDyXjPwMLHYzJpNxRGto4ZXzsLsceLoHAMnKjy5NOqbP7eHUgTPU7j9DT7snaf9okFLSdLKF9np3wvbGEy2cPdrIhNJcLLEVKbW6kmzeem5fPL45GlRV5ffffJh/XPVdTuw+NeIxB7ce5U/fe4KH/+Ov2u9pnKMrjXeg6WQrx986STAQxt3YTWdLN35vgBf/V8vIOPLGcdrOdNDr9hD0h7RitIEA7vouavae1lJCw1H6u71E/CFUVZs5hwIhult6ycxLIy3Hhd8boLfDQ9AXJDAQxNfnp6ejD6Q280rLTkVREwfaaDiCK9OJw2Wnu7UHmzM5nc/isBLyh6jeWcOpA2fiA88gwig4e6SB47tOatk1DlvSOewuW9z3X7GoHPWcAT8aUSibWYTFFuuFJSXe7gFtvSBFpae9D1XR3DvpOalEQlHNxZVwLVptgt1pQ0rJ1oe3449Vc6tRleZTbfECvrScVPq7+xOUl5TQ3daDxW4h5AsRCUUJ+8NaZ8MYQV+QYECLA6Vlp5KRm4YyXA4VTDYTVqeVgvIJhAOhuNspfoii4uvzU1g+gUmzSrDaLFoKcwyjyYDJZKRoWiFmq4nWunai4agWlEfrfxUNR2k7M5ROnZLq4M4f3kbZrGImzy7hrp98AotlyAqKhqOx6xDDut5rLVhAc4H2tPYSCWjJD5FIlJA/zJHXqhMC2SaziXmrZ5FbnJOQDdTV0kPQH8LqsGrnjURRFa37QUqagxO7Tyec4/Zv38zXfn83xdMSYxEAfR0eOhs7CfpC9Pf46G7tSbDKASbNLOZHz/8r39n4j6y9Y2XSOWwOK/NWz6SoooCZyyoTapXiCIHRaIjFPd5dI/L66iYe+eFTPPKDjXELF7SEAIvNnOSGMpmNqIqakAqvRBVq9tTScjqxGHOQ/p4B3vjrLlrrOnj5j6+NeEw4GEGNqoRDEVT13V3LB4muNGKoqvalnZst0tXcgxJV8Xt8hINhQgPa4DlYQdrb1kdPex9Bf1BrW+HxM+AJ4B8I4Ovz03SyFbvThivbhafLSySkBbD73P2UV02i7kgD89fMxtenBVIjoSjRkPbQ+jw+KhZOpr/LS/6kXBwuR4JsZouZkhnFNJ9sJSMvHZPZiNEy7Cs1QHquC4vNTPOpVlBl0vUNLolQd7CB7IKMEf21QghyYjPC8vllYEg8xmq3xPPn80pyCAUjCTOmcCiC0WLCme5g+pIK0vOSg5YSSfG0QvJKc2g62cKJPacSquZtdgtP3bcJgJT0FFJcDgznyJGSloISiZJbko3ZatLST4dfqiq1PleFmSxYOxuj2UA0lKgUohGFmcumcXznSSZOLcDmPCd7ym4hf0o+1TtPsXj9AkpmFGkD19CFUFw5kaUbFmI0GmMNKu3093jxdHrp7/GSkmanvT6xTmdq1WQmzymlYtEUSqZPTNg369JK0nJTSc1yYbKaychNI3NCOmUzS+Lfj6IoGM3GuNIyGLSixuEEfEFef/It2us7eOmh15K+A9AUWHZhJpkT0rX7K+HcX0R9dROHX6smHEy0OHvaezmxp5Zpi6aQnptGcWUhJrOJo2+cSPqcSXNKmLls2oj1EaDN7NNzkpsqgmYZHXr1GK2n22k708GhbUeTFBNozRP3vnxI++2PwEDPAKf2nubU/jpCw65FxBZXHA3Vb55k433P89iPn8Hbm7yQVGqmk0VXzyO7MIPLbx252HDhlXO58Wvr+di3bhjRZTreuOiVhpSSYztr+M3X/sj9d/+OXyWjWgAAFh9JREFUP3//yQRzdUJZDqqiMNDn0+onBLgbuphQpvnT80pzCAXCRILRePqnGlUJBTR3jdliwmAyJmXpBP0hUjNT6e/yMnlOKYuvXZAw0CpRheyJWaz62KUIg6Clto3MCekJT3D+5DyaappRpWTRVfPw9wcTUiBtDit+T5AFV8zFYrNgd1o5d4VOKSV2pw2L3cziaxck+NIHiYSiLN2wCCEEBoMh6Ydtd2nWiSPVTlZhJjnFWQkzJiWiUDQ1n+LKieRMzOLmr19HRn5awjkqL5nKTV+7FoPBQEN1MwYEdueQ1ZOao7WOAFDCUVJzUskYVoVuMBlIy3aRV5qD2WKmfH4Zdpc14eE3Gg1kF2YwY9k0yhdMGjE7yNfrZ8bSCuqPNTH7sunMuWw61hTNhWU0G5mxtIIFa2bh7/eTkZPG0g0LsQ07j8VmoWrdHBZfrS0mVT5/Ev09PmRsAJeKpL/Hx9SqxHz92v1nObr9BAe3HqOxJnGQmzy3lKvvWoPDZSct20Vabho3fvXaeBV+bnE2pbOKwDBU8GZzWll8zfyESYDVbmHy3FJSM13MWDaUipszMQu7y0bAF2RCWS6zllcy+7LpGE1GBjx+pi8ZCkL7PD6e+p/nefHBVzn06rEEOVtq20FC2exSpi2aQuXicjInZHDinLoVv9fPf37iF/z7hp/QdJ4BPTXLSTgYxjlCkPv1J97k6BsnyMzPILsggxO7atn26I6EY46/dZK//PhpXnt0J4/+6KmEFOhB+vt8BANhrYjTM+RymjKvjEg4eQIZjSWeDO9jZXfaMFtN2FKsmCzJrl2DwcA//PKz/OLNHzF7xYyk/aBZbxVVk8kuyBxx/3jjolca9dVNPP/bLZgsJnKLs+lza/38B/2WheX5TCjLQ4mqSEUiFa1J3Zo7LgNg1orpI5qUUpEUTM5lYkWBFrg+J3gsFUlgIEBheT5CCCbPLYkHegfJyEsnJS0Fq8OK3xvA7rIl+OhdmS4iIS0wO21xOcs+sjAh08VsMTNn5XQWXz2PaYum4ExPSep5JYxaBfLMSyuZt3oWzvTkh9SZ4WD+6pnx18PTOAGsKdb451VdMSfJW2CyGEGIeBfceatm8eNXvpOw/7sbv0F2oWbN5JXmEI0qCYq2t6033mbEleFk8pwyiisnxtMy03NSmba4nPTcdCw2M+vvXseUOZMSrjctN5Xrv3wNWfmaRWWNpSAPKmKDyUBRRQHuxi4MBoHRaKR0RjFX3LGS6Uunsuq2ZVQsnILZorkuvL0DXHrDYioWlZNVkElGXhrTl1Sw/MZL4g34Vn98OQ5nosvP4bSz6rbExa+iEW3SIVU1oY4DNEti2YZF/NND97L+nnV8689fpnLx0EBuMBioumJu3PKSaPUkc4d9Z6DVAn39gXv4j2f+KWHxLaPJyJrbV9Dn9sS78xqMBtrr3eSX5SZ05TXbLGTkpmF1WMg6Z5CzOiwIBE01LbScauPErlpCwTCOtEQLueF4MzW7ajl7rCmhOn44rafbsTmstJ5OjImEAiEOvVpN8bRCqtbNZcEVcyipLOLo9hMEBoaKao+8fhxXhpO80hzsKTaO7ahJ+ozUzBSyCzLInpiJbdh3VDStkCnzymg/644vSTDQ58Pd2M3ycyrly+dP4s4f3san/uOj2FOSXbv/P3LRK41D245hd9mxOawIIUjLdhH0BWmobgK0B3Jq1eSkKumFV2ndQbMLMskrTV6QxmI3M3fVbFIzXUxfOhV5jo1vsmgBy8Hiqx1P7+Fcz1HNrloG+nwE+gMUTJlAwBuMz1gBvD1esosyUSJRDAYDl996KZ/6wW3xQfC6e6/kI1+8OubGKmL+mtnYzvlh2xw2Zq+cQfm8Mgqn5FNeNRmTdchlYLabqKiaQu6w3jzDg7hAwkz7kmsXsOS6qgSXhtls4uq71iS4XcqmTdTSHVPt3PXT2xM6jE6ZV0bhlAnxJoIAAX+Ia+7Rev/MXF5JJBxhytwSckqyyMhLo2JROTa7leyCDLIKMknNcnHXT2+nZPpETGYjKekp3PGdW+Kpm0IIsgoyKJ1VpBWZpTrIK8khMz8DZ0bK8FAIzbVttJ5u5+zRpvg2KSVmq5mUVAcWqwm7y44zPQWjUSTMjlNSHXz9wS8MWYgCvv7gPaSkJg6kVVfM4TM//jif/687kqyQQWYsncbH/uUGCs/p2KooCjue3q25QTNSSM1woSgyoc3MIPYUG7nFyS1ZKqqmcOs/X092YSbuxi78/X6WXFfFzd+4Lq4AQatb+sR3b+Hun3+SyXNKE85ROqOI1Gwngz4tR6qdsD9E1RWJAXN3YycGoxaf6WnrGbHNzOrbL2PphoVsuDdx/fpoWHPdGowGbA4rNoct3kEhMszVmJmfgb8/gKJorUsyJyT3e6pcPJWPfesGbv/2TQl9zQwGA+vvuYLLb1tGJBKlo7GTlDQH13/5ahaum5t0nuzCrPiiWxcDF32dRiQUwWg00FjTgruxM75Az/ABy2g0YDAZ4plJJouJ0EAQu10bgBddNZ+Ohq5YO3GN3OIcKhZqOeJrbl/BoVeraR7mdnCkOrj5H6+LFyW1nm7HYBCJfmgBPe192JxazrrVbqE+lgoK4ExPIb8sj9RhhU0p6SkYjQZUVXM7DQ4ORqORj3/7Jjpbetnx1K54I8DZl83gju/cEk/3nL18Gge3HCYa0q7FarMwf82s+OproCnE4ZhtQ69NZhMLrphLXulm2s9qfvsp88qS8ttVRSWnKIu03FQstkQ3kcFgYPXtKzix6xRBfwghBJl56Sy6cm7sfKVULi7n+FunyCnM0poPmoxEwhFu+MxQs8AJpbn8aPO/cnJPLVkTM6lYkLiOxbLrF9Pb4SGvOFcLUhuNWu+lBZNxuHYQigWHu5q7CQcj8RRTVVUxGAwUVxbicNm54avX8uuvPEQ0EmX9PevijfcGWXzVfO766e1s+/N2Vn9iBYuvms+5GE1GLrspuYfXaOhs6kaJKOQV59DT0YfBICiqKKD6zZOsuX3FqOsKSionUlI58R2XALBYzSP63i02C7f800fYsXEXpw6cIbsgk+U3XpJQvBcYCLD3hUOs/OgyhBC4G7tpPtVGSWViHCcrPyPeaHM4jlQH+ZPz6G7pJSNPu8+ezn5yJmYltN259IbFeHsHaDzeTMXCKSy+Jvmem8ymhIafwzFbzCy6aj6Lrpof/751NC56pTFjWQXP/fplmmpaUFWV5pOt5JXmJsyK562aybO/elGbyQjIK8kmddjaDVd/djWv/mUHIV8QqYI1xcKMS6cxsVyrRLXYLHzpV5/h6PbjdMXy9+/95Z1MLB+qQJ1QlovNacPv0QZrg8mANcVKWra2kIwrw0l3q/agDPT6sDqsWlYNMG3R0GAY8AQwmk0YpEwKVKZmuvjnh/+BnwjJgVeOMmNpBd9+/KsJlcerb1/BW3/bT/WbJxFCizVcdktiymNFrKpYVVRMZlPCmh2DTF9aQW5JDrYUKxm5ybM8o8nIkvVVnNhdO+LiOEUVhUyeN4nWujYcTjtTqybHH1yj0ci1n1/L1KrJHH6tmoA3QOmsIuZePitpwM4uyCT7I4uTzg8wc9k0rHYL+146RNAXYsayacxfMwujyciy6xfx4h+2kVucw/QlU6nZc5qJFQWoqqSjoZP5a2bFs3pmLKngl7t+BHDegfaWr2/g5q9dN+oB/EIxmUzMXjkDT2c/RpMRZ5pjxMDsaPh7BsiM3DTW37NuVJ+RkEAwSoQQXP3Z1Wy873k6GjsRCFxZTq79/NqEe+tw2eOFon8vusJI5KJXGpWXTMXd2EV/Vz997n4yJqRz7d1rSc8ZGnzmrZ7NvfffyeYHXsGV6eTz/3VHwg+pcEo+6z59Oa89tpOgP0z+pFxu/tr6hB+xM93JF39xJxvv30x+aS6XndMZdvXHlnNsx0lO7qlFjSpkF2Wx9vYVcUtkwxev5Pff/DMWm4WsAq3xoMVu4co7VyW0Wr7k2vksunoe/n4/V925Kul6LVYz33786+e9H6mZLr7628+z4+ndGIwGlt+wOClr65Pf+ygdZ910tvRQXFnIjV9JbHEwsTyfaQvLOW3Sgo/Lb1g8or93xU1LWHGe2fXkOSUsXDeHltN5CCFY9+nLE+75YPO8wcV53g1CCKYumDxi1fCcy2YQHAjGejwJZi6rJBqJ4m7sYvaK6Umz4NEog/dLYeQUZZGel8ZAzwBZ+RnImGK7ZP2CcVe9bHfaufSGxWzfqNWQlM+flDB5Gg2ZEzK480e30X5WS1iZUJp73iwsnfcekZSC+SGnqqpK7tt34VWbPo8Pn8dPel76u0p7C/pD7HnhIB63hxmXTmPSsDUGBpFS0l7vJi07NantNEBXSze7Nx/A2zPA/DWzmTKvLGGg9PX7efmPr1Gzu5YJZblc87m1SW24Pyj83gD93V4y8tISLJVBFEWhu7UXs8X0rtcPUKIK3a09WB3WEXsLfRD093g5ta+O3g4PKWkOpi6YFA/Yjyd6O/p4/vev0HamAyEEsy6t5PKPXTpuUzh7O/qIhKNkF2bqM/lxghBiv5RyZH/d8OPGu9IQQlwJ3A8YgQeklD9+u+PfrdLQ0fmwM5jlY7KYLppMHp33jtEqjXHtnhJCGIFfAWuBZmCvEOI5KeXxt3+njs7FhxDivM37dHTeK8a7XbgIOC2lPCOlDAOPARvGWCYdHR2di5bxrjQKgaZhr5tj23R0dHR0xoDxrjRGSv1ICsIIIT4nhNgnhNjX2dk5wlt0dHR0dN4LxrvSaAaGr284EUhqViOl/J2UskpKWZWTk3Pubh0dHR2d94jxrjT2AuVCiDIhhAW4FXhujGXS0dHRuWgZ19lTUsqoEOKLwEtoKbcPSimrx1gsHR0dnYuWcV+ncaEIITqBhnf59myg6z0U5/3kwyKrLud7y4dFTvjwyKrLqVEipXxH//7/d0rj70EIsW80xS3jgQ+LrLqc7y0fFjnhwyOrLueFMd5jGjo6Ojo64whdaejo6OjojBpdaSTyu7EW4AL4sMiqy/ne8mGREz48supyXgB6TENHR0dHZ9ToloaOjo6Ozqi5aJWGEKJICPGqEOKEEKJaCPHl2PZMIcQWIURt7N+McSrnd4UQLUKIQ7G/q8dYTpsQYo8Q4nBMzu/FtpcJIXbH7ufjsSLNMeVtZH1ICHF22D1NXhB6DBBCGIUQB4UQm2Kvx909hRHlHHf3UwhRL4Q4GpNnX2zbuHrmBzmPrGP+3F+0SgOIAl+XUlYClwD3CiGmA/8MbJVSlgNbY6/HkvPJCXCflHJu7G/z2IkIQAhYJaWcA8wFrhRCXAL8BE3OcqAX+MwYyjjI+WQF+Mawe3po7ERM4MvAiWGvx+M9hWQ5YXzez8tj8gymr463Z34458oKY/zcX7RKQ0rZJqU8EPu/F+3HXojWev2PscP+CHxkbCTUeBs5xxVSY3BRanPsTwKrgL/Gto/5/YS3lXXcIYSYCFwDPBB7LRiH9/RcOT9kjKtnfrxz0SqN4QghSoF5wG4gT0rZBtqADeSOnWSJnCMnwBeFEEeEEA+OB5M65p44BLiBLUAd0CeljMYOGTet7c+VVUo5eE9/GLun9wkhktex/eD5H+CfADX2OovxeU/PlXOQ8XY/JfCyEGK/EOJzsW3j9ZkfSVYY4+f+olcaQggnsBH4ipSyf6zlOR8jyPlrYDKae6UN+PkYigeAlFKRUs5F60a8CKgc6bAPVqqROVdWIcRM4F+AacBCIBP45hiKiBDiWsAtpdw/fPMIh47pPT2PnDDO7meMZVLK+cBVaK7eFWMt0Nswkqxj/txf1EpDCGFGG4gfkVI+FdvcIYTIj+3PR5uJjikjySml7IgNfCrwe7RBelwgpewDXkOLwaQLIQYbY47Y2n4sGSbrlTFXoJRShoD/Zezv6TLgOiFEPdqqlavQZvTj7Z4mySmE+PM4vJ9IKVtj/7qBp9FkGnfPPIws63h47i9apRHzDf8BOCGl/O9hu54DPhn7/yeBZz9o2YZzPjkHf+QxrgeOfdCyDUcIkSOESI/93w6sQYu/vArcFDtszO8nnFfWmmEDh0Dza4/pPZVS/ouUcqKUshRtWYBtUsqPM87u6XnkvH283U8hRIoQwjX4f+CKmEzj6pmH88s6Hp77cd0a/X1mGfAJ4GjMtw3wLeDHwBNCiM8AjcDNYyTfIOeT87ZYCqME6oHPj414cfKBPwohjGiTkSeklJuEEMeBx4QQPwAOoinAseZ8sm4TQuSguYAOAXePpZBvwzcZf/d0JB4ZZ/czD3ha02GYgEellC8KIfYyvp55OL+sD4/1c69XhOvo6OjojJqL1j2lo6Ojo3Ph6EpDR0dHR2fU6EpDR0dHR2fU6EpDR0dHR2fU6EpDR0dHR2fU6EpDR0dHR2fU6EpDR+ddIITIEEIEhRBSCHH7WMujo/NBoSsNHZ13x8cBC3CW8dOaXEfnfUcv7tPReRcIIQ4CPWgtJ/4HKJdS1o2tVDo67z+6paGjc4EIIeajdRn9I/AIEAE+PcJxRiHEt4UQDTFX1hEhxEdjq6/JWKv74cfnCyF+LYRoFEKEhRCtQojfCSHGS6tuHR3d0tDRuVCEEL9Ca2yXJ6X0CSGeQmv/XRLrPjp43K/R+i29italNAe4F82ltQAok1LWx44tBt5Cc3n9AW0tkinAPUAHUCWl9HwgF6ij8zboSkNH5wIQQtjQWpE/J6X8VGzbBuAZ4Gop5QuxbTPQOpC+FNuuxrbPQmveZyBRaTwLLAHmSymbh31eFbAL+IGU8rsfwCXq6LwtuntKR+fCuAHIYGh5UIDn0dZguHPYtmtj/94/3PqQUh5FUyRxhBBpseOfA4JCiOzBP7ROpqfRWmPr6Iw5F3NrdB2dd8NngE6gWQgxZdj2LcDNQohsKWUXUBbbfnKEc5xEW41tkAq0CdxnOH8m1pm/S2odnfcIXWno6IwSIUQZcDna+hCnznPY7WjZVCMty3reU8f+/TOJFsxwAhdwPh2d9w1daejojJ5Pow3wdwF9I+z/AZql8D9owW7QrIhzrYSKc16fRltUxyKlfOU9k1ZH531AD4Tr6IwCIYQBLb7QJ6WcfZ5jvgN8F23dZj8XFgjfBKwDlkspd51zXgFkSyk73/ML09G5QPRAuI7O6LgCKAI2vs0xg/s+I6WsBn6HpgheEUL8gxDiP4DX0JZoBc26GOQetKysN4QQDwgh7o295z609Nt737tL0dF59+iWho7OKBBCPAncBMyOZUCd77iTaOs75wNh4N/QXFZ5aAHwH6BZIl9Hq/NwD3tvNtr63xuAYiAINAHbgN9KKY+/91emo3Nh6EpDR+cDRgjxN2AVkCqlVMZaHh2dC0F3T+novE8IIewjbJuNlm67TVcYOh9GdEtDR+d9QghxN3AHWvFfJzAN+BzaZG2ZlPLg27xdR2dcoisNHZ33CSHEIuD7aM0NMwEvsAP4npRy/1jKpqPzbtGVho6Ojo7OqNFjGjo6Ojo6o0ZXGjo6Ojo6o0ZXGjo6Ojo6o0ZXGjo6Ojo6o0ZXGjo6Ojo6o0ZXGjo6Ojo6o+b/AU18URmcxZ61AAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"area = np.pi * ( X[:, 1])**2 \n",
"plt.scatter(X[:, 0], X[:, 3], s=area, c=labels.astype(np.float), alpha=0.5)\n",
"plt.xlabel('Age', fontsize=18)\n",
"plt.ylabel('Income', fontsize=16)\n",
"\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x7f4a9de59208>"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from mpl_toolkits.mplot3d import Axes3D \n",
"fig = plt.figure(1, figsize=(8, 6))\n",
"plt.clf()\n",
"ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)\n",
"\n",
"plt.cla()\n",
"# plt.ylabel('Age', fontsize=18)\n",
"# plt.xlabel('Income', fontsize=16)\n",
"# plt.zlabel('Education', fontsize=16)\n",
"ax.set_xlabel('Education')\n",
"ax.set_ylabel('Age')\n",
"ax.set_zlabel('Income')\n",
"\n",
"ax.scatter(X[:, 1], X[:, 0], X[:, 3], c= labels.astype(np.float))\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"k-means will partition your customers into mutually exclusive groups, for example, into 3 clusters. The customers in each cluster are similar to each other demographically.\n",
"Now we can create a profile for each group, considering the common characteristics of each cluster. \n",
"For example, the 3 clusters can be:\n",
"\n",
"- AFFLUENT, EDUCATED AND OLD AGED\n",
"- MIDDLE AGED AND MIDDLE INCOME\n",
"- YOUNG AND LOW INCOME"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<h2>Want to learn more?</h2>\n",
"\n",
"IBM SPSS Modeler is a comprehensive analytics platform that has many machine learning algorithms. It has been designed to bring predictive intelligence to decisions made by individuals, by groups, by systems – by your enterprise as a whole. A free trial is available through this course, available here: <a href=\"http://cocl.us/ML0101EN-SPSSModeler\">SPSS Modeler</a>\n",
"\n",
"Also, you can use Watson Studio to run these notebooks faster with bigger datasets. Watson Studio is IBM's leading cloud solution for data scientists, built by data scientists. With Jupyter notebooks, RStudio, Apache Spark and popular libraries pre-packaged in the cloud, Watson Studio enables data scientists to collaborate on their projects without having to install anything. Join the fast-growing community of Watson Studio users today with a free account at <a href=\"https://cocl.us/ML0101EN_DSX\">Watson Studio</a>\n",
"\n",
"<h3>Thanks for completing this lesson!</h3>\n",
"\n",
"<h4>Author: <a href=\"https://ca.linkedin.com/in/saeedaghabozorgi\">Saeed Aghabozorgi</a></h4>\n",
"<p><a href=\"https://ca.linkedin.com/in/saeedaghabozorgi\">Saeed Aghabozorgi</a>, PhD is a Data Scientist in IBM with a track record of developing enterprise level applications that substantially increases clients’ ability to turn data into actionable knowledge. He is a researcher in data mining field and expert in developing advanced analytic methods like machine learning and statistical modelling on large datasets.</p>\n",
"\n",
"<hr>\n",
"\n",
"<p>Copyright &copy; 2018 <a href=\"https://cocl.us/DX0108EN_CC\">Cognitive Class</a>. This notebook and its source code are released under the terms of the <a href=\"https://bigdatauniversity.com/mit-license/\">MIT License</a>.</p>"
]
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