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"source": [
"<center>\n",
" <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/Logos/organization_logo/organization_logo.png\" width=\"300\" alt=\"cognitiveclass.ai logo\" />\n",
"</center>\n",
"\n",
"# K-Means Clustering\n",
"\n",
"Estimated time needed: **25** minutes\n",
"\n",
"## Objectives\n",
"\n",
"After completing this lab you will be able to:\n",
"\n",
"- Use scikit-learn's K-Means Clustering to cluster data\n"
]
},
{
"cell_type": "markdown",
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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",
"\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",
"In this notebook we practice k-means clustering with 2 examples:\n",
"\n",
"- k-means on a random generated dataset\n",
"- Using k-means for customer segmentation\n"
]
},
{
"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>\n"
]
},
{
"cell_type": "markdown",
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"source": [
"### Import libraries\n",
"\n",
"Lets first import the required libraries.\n",
"Also run <b> %matplotlib inline </b> since we will be plotting in this section.\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
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"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/sklearn/utils/deprecation.py:143: FutureWarning: The sklearn.datasets.samples_generator module is deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.datasets. Anything that cannot be imported from sklearn.datasets is now part of the private API.\n",
" warnings.warn(message, FutureWarning)\n"
]
}
],
"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": {
"button": false,
"new_sheet": false,
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}
},
"source": [
"<h1 id=\"random_generated_dataset\">k-Means on a randomly generated dataset</h1>\n",
"\n",
"Lets create our own dataset for this lab!\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"new_sheet": false,
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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>\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"button": false,
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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",
"\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"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
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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)"
]
},
{
"cell_type": "markdown",
"metadata": {
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},
"source": [
"Display the scatter plot of the randomly generated data.\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
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{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7f86dd6982b0>"
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"metadata": {},
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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,
"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.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"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",
"\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>.\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"button": false,
"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,
"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>\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"KMeans(n_clusters=4, n_init=12)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means.fit(X)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"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> \n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 2, 2, ..., 1, 0, 0], dtype=int32)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"k_means_labels = k_means.labels_\n",
"k_means_labels"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"We will also get the coordinates of the cluster centers using KMeans' <b> .cluster_centers_ </b> and save it as <b> k_means_cluster_centers </b>\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([[-2.03375169, -0.99827293],\n",
" [ 3.97334234, 3.98758687],\n",
" [ 1.99876902, -3.01796355],\n",
" [ 0.96959198, 0.98543802]])"
]
},
"execution_count": 8,
"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,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<h2 id=\"creating_visual_plot\">Creating the Visual Plot</h2>\n",
"\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!\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"Please read through the code and comments to understand how to plot the model.\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"image/png": 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td8OBtjF7Hpc6xA1r79x/ZovcGaEIWOH2xdX+cl7F50Q2b/2dbOjl0lYwwj3C8hU0uLYvybFQWcdIt2kPMNHOiCl2GahZD9RuBA2+B23lx1z5IOiTdYkwOQpUrfK3G9duApas8kYPLdvIHAxDB90K9ctehRrt9S/m1W9jFW7LQ8DEGebQuPt3pGp5j5sNcVeeJLVA1T9yhDk4NnyeVdCrdrLGlOQINDOeHcE5dnJu3/0id0YoAla4fXG1v5xX87nEEKisBho5biNFExA575Fl3Z3+JglygMh51tkW7WVEt+ELoCWroEXOAg3boVXUs2rW55Nd7cY5tgAZh+m7RH45ASFgphtazTo2st6tuFkTCRi5EgH6BCPrDGs/RsvD0EIhoG4zyLaB+q1sEbB6LYCwS8qnQef/HtqGX2N2NTis4WPZBkHIXpD8A+zcE0NS+DvYYh9C4iYQlGO0rf/WexKYBYvdGaEW4RRuK8gLOsUu5HDPac5ZarN9buwki22MX2GElxwFTbSzScSiA24vcxlEOkFWEkhHWJV9/nlg+AgjL9ftoFkpRnzuyCAMHwbciRUsq4HHOYqzYK+lxkA16wAjAaQnRFsxTZxmZD9ziS3INe1mft/hw0D5ciYxaCGgpBwYeo9FXU51AWSyBboV97D3YLNtxWy5PezYkx1MIkkOghyLSQxks+NGOtl3WbteWvx8AFpJKbDibiB2mUk08jilkQ9ApVXs5lTgZ3uzQFXACrcX5iAfCL2xcXfuFuPZPte0hy2IRTrZ55vul7rlSliV2bAdQIhNnKi/i/l/K1cw/6xo1igFWh9lWb9Dh9g28rSM2k2AY4DSk9CSI1Jc5YOe7rt0NbSJ00B9I4BaNnizfiu06rWu28H9zModwLirA5dVS4tru0ETZ6ABzC88egzaql1AaTUjcN7dt/XLwMp72RcxfEhqt97uSQxTF6Bt+ldAZZ2/mYJXyBl2Q8DSFjfxbR3zRrtyjG8681X+bBcLFAEr3F6Yi3xQKJNhts9NnIbWuJvlJzTtgVbVyJLL+MSJ5ZuZK2HyNNC4B5QJCRIi22R6cfODolOObINVqXf/DqCVMgmgcTdzLlTWe1ICiHW0Ne52mx0k3Xd5GyPDZXewCpOIEaik35KZgMYX5nzNHoC2/nOsFTg1xmQCfm5jJ11XhgbUbWEjlTKWT1Jg58L1bfZZkTksRVmKnIymvUzvXrbRlUMm3bbtkvwz5pr3SbGZNwcUASvcVpiTJii3DM91rE7D3WxUkLTyT5X1gug0Oy18thpCwIp7QOFK5rlt3A0aOsiOzclGDmKvXgMsbQalp6DVbvAvwmUspq3G+jw/bsPdoKlz0FKjjFSJ2J/UGFBRCxhx9plQCTR9kvl7G+9309b4XLj7WaOFFWcV+mQ7qGE726b+Ls+VQQ60cCVQv9O70emTwPI2ttDWtIcdG/Ayh+u3sZwIKw6ULhGVNtOcWfAPqltcieFQTgfEYreb5YPSgBUU8qAYrTe37kiutWwb87w23c+0zNhlt7LrZ2TWtMcjpfBSf1Tkpn8lpheTbXgaaeNuNh5+5ANomgaEl7jvfZ5V6DVrGBku2wAY02yxKmNC06fchSuNnV/G9PTdiuUAd0HUrGNZFOMnWbxlqIyljjkWW9QLL2E5FPVbATPG9hUq8XzRGYuRfGqUEXI6ApTXAYlhFvY+3QVEOti2kXOs+cOIAXBYKhsI2uYvse8p47Aq2bHZ9+e2H2PkA/aa/L3PR4PMAkARsILCtcCNoPT94gsy+BDaqh0ANKaHLm1xyXEdUFLmLbpFzgHpcfYY7xKyVt3s614Tc9y0EjddbC9Q1eCSFg/aKQEQAmruACY7QGMnshawtJIws8GJ1z5kJJwYYgHsI0eBigZoK+9lZDx0CCCLTb4gmx2r4W7292Q7xOy25BB7f+wjpgkvXeOSfJf779UAZaCVVLCKd+Bd7wZVWSc0ZIwchbZkJQtmj5z1AofIlVz4DcvNkhDf+03amqwkCAWFq0TeCMqC8ZP73IWlDcwraya8ylQ8xmeY00B6RBdIjTKyJQcYPurayjJuqM4eEDS2eFa/FVrpEjfcp8nzEwNe4A9CbqVpAvEB9zpCzPsbKgWWNLqLj8Q8w2bCzZXQgGHpmlbtYr7moUOeTNK01yexaK2PssW1pS3S9+E1ZZA85ojDN9VZY5GYbnwn+dwWi99ulg+KgBUUrhZ5urvkxTQaO+nXUZPDwLKNXgyl3BXWsJ0lls1cYotTyRHRfUb1dwpnBYxp8fiuVa91my/cxcLmfcxyNnwY2ppPsirbTkGr3cSqSrhBOyhjzooMkx4EcdZuAmrWsn1XrXIXH5vZQhm/EcxckjzLewGEWYRl8z5otRuByhWg+IC3mNe4W2pE2ebvbHMsZlWrvwtYeR9YFc+/EJK+O7+2OxfCnYs+nGvb66kvKwlCQeFqEXjszdKDR44wL68InqmAVrMWICe3X3X4fTbLrXE3tIbtrkb8BVYJylJHRT1rId7wBTYZo9GVLhp3s0f1mUvMsVC6lFXRGRuorAdNXWBeXNtm52qlgInTeOHdy7j7yX9EeN3j2H7vx/DCd/4vZjFr2sMkkFg/y59ww+GxtMXthntYhPSIUUEVdQAArWwJm1tXvYaFBo0cASWH2U1r7ARrPEGGfWb5Jlb9gwBNY/pufIgFDrX/DVC9Zs7E5xtxNBd9ONe211FfVhWwgsJVIqsKC/pQ5fZdGVL4DK24200Qu4ttv6SJNTZUNTJSanrAHUPkSh0gFtq+ZDWrVskBprrcXIgZL7MXYE0Srs0MsX5GnMOH2T7drIkX/va/4D98/xi+9/VHsW97Mw53DOPJv/oboG4zvvSJO6HVbWGeZa2EZUrUbQGmzrm5EW4r8n1/Ko2ud0PZa9YCGQKWNrmaNffvbmWZwxW12WHxGVMEzKNyOVDpVr/F2v9k8PFQuUYcFUKuba9jO7NG3BJSBHbu3EkfffTRvJ+EgsLNhHyPpOz1D2a1rZFtuB7X9ayiXN4GTHdDW7WDdc0lhoD4ACO0e//Akxg2fIGRarjSDavZxh7rG+4GzARgp4CKZcDoRy5ZhDxPbSjsSg372X6aHwIyBrZv24z/7+/vxsd3tIrze+fUAP7wu6fQ/uIfsPzhFfeAprqYvAAC0hPsBkE2u97mfWyhbuRDV5MuYTa4ZevdpLZNnp2MfwdjJ1nlO/aRK2OUAJF2t43588xqV7025wh5udHFF9oTfN8NiGeSy8JC07QTRLQz+LqqgBUU5oo8HVfF6JJkG2whrWad1xk2fRFouMfb98QZFg8JuPkOTayybNztZgG7vt+tX2aOB8qA9Ai06tWs0m1+kOmqdVtY0A05wESnpNuyacnQp3G+dxj7tjf7znHf9mac7/4naHf/Lnth6BC0pj2AEQWcJLCkxZ09t9LLjeDt0JMd7MZQs5bp3dVr2OJckAx54lnzQ4A+BZTXAA33QNsQ94gzQL5kG+7NiWve5AUK1W/zkuQinTm1+Zw/iwX2DisNWEFhrpiD5SlLF450stZgbrsaO8GIh5NN0142Ul4rcSu7MgAh9livhdhn+CSM+m3QKuuYNa26lRFa7QamJZ9/nvmJ13ySuRHOP8/eb3kYiF0BQKDhw9i6nskOMg53DGPrhtWAlRJkz7TnOqCqmXl9Zy4BcG1pBHa+/LgjH7B/L2kRbc4Y/RBw0iAz4T0BrLiHVc5TZ12LWphNAimtyqpahQ+491VpEsheaEuamQdZ1mmDU6bzYRF4h1UFrKAwR8zJ8hSslhvuZhWfNPlYrvS0cAWo5WFgpptVt+7xqHoN6zJbtYvNfAuVQotdZqPmeV7FzCVoS1f7oyFDpd6/67eyZopl64DJdmgbfhV//h91PPnnX8f3/uRhTwN++iD+4i//s9s4ssdrbdaITcCI93s5xdWtTKOlsP+4vBJu2uteJ5+e7FrnqltZVObMJa8bsPVRf2wnOW4C2l7WrMGHhGolrp2vm6XClYRdG5vmfZ++zOFczgbTn2u8QFAErKBwPRFYwNFKwqCKOtZIYCWhRc6BqluBshpBDlqoxI18NEF22tVWH2D7i19heQw164CqlazqnDjNbGYbvuAPAYLGutsadwO1m0DTF6Et38w8w407gdgVfOlf/zoA4A//P3+B85d+iq1t6/EX/+kZfOmRVnca85eZPKKVADM9QLXkK27czaZetDzEFuUyIaBln7s49/eu1vwgG3ufnnTJdr8gbur9GbS7f0fIIsKxYCVYToaP6NcA5dWsm06fhDbV5erinwc1P1T4pphLMho5wr639b+6oK3LioAVFK4jchGDVhIGNWxnlWH9VqbT6lOCdMXCmRlji3FWAlp6gvl7Q6WMkByDjQlq2gutcTerFCuWi0xfreFuX8MDmvdBq6jz9GM+fmjkKL70xX+J//HhFmgtD7KYR7f6ZFXznYx8AabrRs6xKr7lISBjM/Ktv5MRffM+Fsa+fLNni4v2QqvbyixxIuGNVcPaih0ADwpCiGVBNO1lnmNfA8n9LhHvYpY0I+ZV5qt2smo7X0APkMfZ8MDVOyzmEUoDVlC4wWBjiDrcDrgwtPQUa34YeBeAA0qNscWmijqm85YuYQE49dtY0A2IhbqTA9KnJJ31GGucaNoD8MdxEYDjAFPnvdca7vIGcY4eg9a4C0iMgEJhRtwdf8vmzIHYYiHZLBeiahWQMRjhIsQqX65n82uavuTmRxhssZG3LFs60PKQb9ozIp3M+0wOs+NBc9u3Q8z21vwQ+47Wf45V/+RAq9vMmkqaHwKmu7NtfgHImR5ckwdoUQz1VBWwwqKBnrbw3puX8MgnN6GisnShT2fe4GmQDwAgVuG6o3fQsB0UCkMb8QZdaht/nWUrQGOh5HLHm5WAZka9Ft/6bX7tFQTE+lk2cLiSyRzpCJAaZWN+Spe4iWjI1kDjV5jbgdWGrsRxRDgO0PKIO97oEHNqVK9lVbHsdzZi7v5dQhVZygCa97KJGfKiIx8WKjKJNXcMUSlQzavTEtDA+1kyglYSLlz55sIiywxWBKywaPDem5fwwvdPAJqGT39u60KfzlVDLCQ13M1Igv/S+2a2gRHy5FkWKVm70bOaAYzoht5j5Hb377GON6klmLc209gJaJUrQKs+Bk0rYeE89XdBK68DypawfVatAioboJkxRphamPlzy+vcbAcAQ4c9a1eojIW8Z2xpsXAvC+SpWQs0P8xanic7gEwLkLGZ5hzrByob2PlnZSk3s0W35W3A5BlBwmKBcWmz72ZAtsmChJauZo6I+WqGWGQz4hQBKywaPPLJTYCm4ZFPbFzoU5kTslbZI50ixYuaHgCaHnTntDHHgMiFiF1mzgStlOm51WsBuDm98oJV4/1uA8XngfJaABqroFECLWMBNesYSYqhlueYxSvjsA47PtEiNQ4t4Xpza9a6ucA2MHnOV0VrkXMsojJjAyUV7KYQ6we1f9edAbcGWNLIKl4tBExfZJU4NK9hpPkBV2d2r2/yDKuMeeOJ+91o4XKANBZ3yQPX2ZcKGFNs0Q/zF7az2EJ7lAassGhQUVmKT39u680nPwT9pA13A2MfMV00cg7enLYMI4DmB1nDxLINTNMlh3WOVa9hbcWVDZJ+u5c1JazaxTTbseNsf2Mfsb9r29giGddzxz5ilXeohFWO3Mc7egzaxl9zdVTLS28b+YB5d3m2g6MzX+3UeaB0CRDpAI2fZiS/9ctA8wOgaC+z0gHA8PtulkMnEApDW/2Ym9R2mJFvqJy1HJ//e1Yxy9/NyFGW+aARkBxx4y5dxAeA+u0sVvMmmvE2V6gKWOG2xrzozrmsZk0PsBV8dxaaeLxvfohZ0M4/z5oF5NluW7/CKtfkKGAl2Oy1WD9QuhREGWhNe1kI+/D7koyxBzT4LrSWh9wqe7W/g0yetDx51nNArLgXRA4bm1S2lFXE7lh6JIeZjayygWm0I0fZvurvAoaPQGtxg9aFbk1u+Po4ULHCvV7X29u8z9Oa67eyapd/N033M9IdPswmcEijiVCz1vU3u2Pqy5exp4dwxTV3sC2GDjgORcAKtx046T72K5uF7kwEPP7EZpSWlhT8rC9WUeQxnPPNbwP8j7rEmxG4Zarhbmj3fYMtcgH+RayJM2wc0fbfhsabEKBBi3SySney3Z2/BtFooTXuBnNGXGGjiqa63CYOErPlYCaAus2siq3fBgwdZENCUQLUrM8iU23rvwWWNPvJvvlBLx/YPa648SSHWedbcsjXZAJyADPpmyEHsEYJchxpHD2zyglIi5JofhB05q9Zh2Drx699IW0RLcQpAlYoiFvRmcBJd1ldFR755CYQAQ88sh4nPhjAnofW+bbNun7eKGBG3ZDyqKvP/lrWL7NXaT3ILFPcpkUOW9CqqGWVbbgc1PwgWxir38bIKxQG6qSQmVU7WIBNXRswddENwAGTDmrW+sLQqWYd8w07BiNzM8a2t5OswpaD01fcA4Qrsny1VFoFLTnsacONO9mCoTucVEuNsBZofs01a9mg0CXN7PNWElrkLFBex8bOZ30nbmOJ5MQQQz4dd/qFWJTUGPnysPZrHb65iBbilAasUBCcrN470J13Gz1t4Y1Xz0FPW0Xtc67bX+vngnjkk5vwpa/uxL33taCishSPfaYNnWeGsX1Hc9a2WdfftJeNdBd/P8ASy6RJDmQboJleSRs+wlb8V+1wdVk+++0DttIPsMf2y68DdpqR9PD7rPNLRv1dTLstr3UDcGzmB87Ybj7wr7qTkpexSck8wrJpLyP98ZNZ26KshpG95U67mL7o3gRCjEyhMW1aC7PzqnZnzlU1Agixbr2Bd1mKmwav0i5dCtRtA5a2iGB6PhePen7KrnvkiOs33gRA8zIzoj0AiC1KuqE8WuvHPflh+LDrib46+aCYWX83CqoCViiIYpwJ+exj+arnq7WbzZdNjS/2cRCA+pVLUVqWXY8Er18Ll3s65aodYiyRr6OKj6Xf/tui0iLbYjm+S1s9XdZN/QLAiLxxN9N/42fcx/KQv6rWSjxfroiplLTW6nWAVgqtsoqRmZAUHvJG+5QtY1UvX7zLOMDI+64lrp15haGxinbqPDR9SnI27PP2s+HzrEXZmGbX2rgbGDnsXpOb1aBPs9zfyQ62UDd5hgUPfex/BaqaXEcIsUXHkSP+bODJDpHz4EOR8sFi0nkLgoiK/nPfffeRgkIQ6ZRJv3j1HKVTpu/1X+zvpC9//nn6xavnito+5373d4rtiv1crs8W8578+tGDvUUdJ3PlHXLe+UPKXHnXe83SKXPlXcpYhvRaijJX3qaMlSq8rxPPUsZMis9nLJ0yoycoY1vs32aSMlfeYa9bafe/U+x9M0UZ26RM5IL0XpoylsX+Hv0o+/XRE+z8s95LUyZ62b0W9xiW6W7ztruNQRkzQZnpbul7eJsyqQi7nukeci78mDK2QZnIeffc2WfFNduWdL7vUsbSC3/f4rudZbscP5eFBICPKAenqgpY4ZoRrCg5Hv10G+7Y1IC16+uK2j6IYMVb7OdyfbaY98Tr0BAuDeH0iSHce19LYQ08h56Y02s68qFX4bU+mrUbcmxPb9XC3rBKHlzuToqg3p9BW7XLS/Wq3cQ8xJEzrnTheoFTY/58XmMaWLGDSQC8M612E6syN3xBtEWLoaHLNjCZIT3JFsGmzkPTI8xLvOaTrhxgMttcw91uNQsRkk6lVcDSVmjxAYBCbH/yBAz3O9BKwkDdZvYl8Dl6A+/mrFzFAmhgwTMnmvayar9he+HtFhiKgBXmjGIX5ihD6Ls0iTXrll/Vca6lMaPQZz/+mbac7+17bAMyGcK+xzYgMplAU8syvP16V0HZo2hjf+Nu1xlwv3gpa7JD3WZ34U3Kwg1MBtZW7WK6anwIqFzltgsfdhcEY55joeVhb7FtwxeYxJAxpSnOIQAhRrYtD4H0aWh6hIXmLNvArHSWO1a+Yjm0qiZgeRu0kQ8ArsVCY5KKprE4ypU7GPmefx7ahs9Da/245wQZO+nGSWrukE4z96SKkSP5JQYuP+RY8Mz1c6H6bey7WcQyhCJghTmjWC0213ZzcVXkqniL/Xzws6Zpw3EI7/3yEh791Kac5x0uLcGGtgaES0NYs45V7fPWnaeVuhXpWTZSPVwu6ZkkCBTN+3wVoJd1C/Ea2QYjxso6aCWVzHPsjjjSymqZ3zY9LnW37QXMGXdSBLeU7QOSg+7sNgtapANo2gsaOgwtNc507uBYeSPGYiQ7/pbNeavdxCZZDB1kBB9ewhbHeAOJjPo7WTVdvUZU8ZDcEQKFHApCO9+Vn8BlLCK7WT4oAlaYM4olpVzbXetC2lwX/Dii02mc+GAAL/7dCQDAZz6fbWEqLw+jbdsq32vcJXHigyvYsZvNTbMtB4ff7pmTNU8Ll3oLYxt+jdnO+Nj2pj3MslW3jUVOBkkjcs6Nocwwcm7cDZpoh4aQm6Owhj3iT7Z789HCTQAAat7HvLlVjUDj/V4bdLSHTc+wksD4SUHMWuNuoKSMVaxiJDzLnED9nazRwx2yCS0sVechVzYJM68uciyEVTNHhLakkZH70pasytTnnw58nudGsBvAjtlJdRHZzfJBEbDCnFGsFptru2utKPN9/vRHg4hFDZw+MYQ9+9ZlfW7Z8ko88qlNAIBH3b9ng562cKVvCn3dEbzw/RP4f//lpwEi9FycxI9/cHLuNxGZEKJuuHl1K4AQG/WjhYHKFdnjdOrvgpYYZDryxGlo1WugbfqXQGUdKD4IDTYwfFQkrFHVKqBqFdNJhw8z33JpL0swW/+rQHqKxURmwKpWX4Vd4d0otn4FWusjoLETYlim1vpxRuqpMSaBiK62vdnXm6MC1cJloIEjYip0wTSzXBXs0hZGvgVIVfYaF5oJtyiQa2Uu3x/lglCYTxRyKhSCadpZLoV0yqTXf1r8voo59i/2d9I3v/EaJeIG/eLVc6TrFum6xf69/1zW8edyLRnbokxskJzBQ5QZPZl7G+FA0L1/CxeE60JITVLmytueA8E2mTPhytuuU8IIOBz87oHMlXfIufwm+4xteec2elI6btrnXmDn8BZlzKT/ekZPSJ8xXOfHO2x7nyNEd/ef+5y87dJZromivttF5oAgyu+CUI0YCguGXE0exTRbvP16F77z9GHf59578xJe/LvCDSOzHdswbCQThjj+o59uw/371iFcGsKnP7cV5eXsgTEykcDjT7Tl9DYXe3zWDXcJ2sqPAfXbQLblH94JZIf8aGEvfH2ENXHQlQOscnWHVAIhd5v9wMgHTCdtuAeioYLVuh6aHoS2+mEgPgiQzSSOjOkb9a6FK0QjBAChDWP0GMhxWBPG8CE3lOcc2yZylskWrmaMkSOgmV6QlQIQYqHr8sDPXIicA4XKWO7EbF+nPPy06YGih6YuOHKxcr4/qgK+eXC11eX12k/efQd8vbm8wzn9wPvPUSKuk65bOfeVryK2LJtGhqJiHynJ89vfG6HX/ulsTu9yofPLdy2FIPy3V96izHQPq4bf+UNfNZzL8yqqTyvFqswr7zI/r2O7floj9+dkn65b6XrHeJvtN3hOtpVdgY+e8Hl2M7YpVeDvsH/zbWR/r5lkHmd33/7rS/uqZ+/c/L5n/zm/k+f6Fk/VKwN5KmBFwLco8hEFUfGkapo2vf7T/PspFnJjw2zH1XWrKFLu6hylb37jtbzn9fpPmXzQ3xsR5/CL/Z2CcPW0RdORJB15t0fs27JsSiay5YXgteQj2lzSSL7vwjRdwjSTLpFZbuPDbI/lBiNH95GeSxmCgAJyhp8036GMEWNNEVaa7UcQl0uekmTgETIjtVzHyIyeYPvkkkfkQk4iZDeLbDmC7yMfeeZsdCnY/FK4QWOhoAj4NkMhoihEzjKOHuyl6HR6TtpqLvxifye99PzJgmReiJx13aKuc2Oi2hXbF6g4dd1yybSTkkmDjh7spS9//nl6/afsXH6xv5MsyxZ6bippkGUxjberc9RfWRf5BHD0YC8deO0C9fdN5f1s8DvNpKYoY8Y9AitARrng657Loat6pHmCVcmjH4mq1991p7NKWp/xtOCg9sv3zW8avMIdPSl9ht8g9JxVbc5rKECeOav5RU62uaAIWEFgLq3ARw/1kWnaOd8vVPFx8tF1S+znam8KVyuD8H2+9k9nyTAsSXLoo1g0TR2nh9l1GBYdebeHTIOR73PfOkJd58ZynlehxT7TtMg0LOrvjZCuW4L05WvyPVXsP8dIUTzCv8sqWqnCnQ2eDOFWxHJFGxv0SwCX33TbguXWX2lxLLC4lhk9QU7Pz0TFm4kNUma625US3vG9552P17rMtlucksCNhiJghXkFJ6LodJqOHurLer/YKpuIXGeBnvfRX96XbTOZwLa9m0I+gmbV7BilkiYZhlc927ZDHaeHxfZHD/bSN7/xmqiYZV04KIlw8nz9p51k206WtHL0YC8l4rpbUds5bzjJpEGv/dNZSsRd0pQqOvGoXlQmQg5XA9+XmWQ5DLEh93Uji3Cz9umrlp3satqnyaZ9TomsfVx5R1TCCioLQuEqUKi5gbsOABZkHkQhv29wv+++cREfvt+PL/7mfTkbGx755CYsq6vCffe3IpNh/+Me+HmX+Lyc4XDHxjq0rKlFaVkJa4XunsSaO5ajrCzsO/ajn25DSYmGDw714d6dq9HcWotDb3WLcPZ4zEB0RsenP7fV5/V9VPISn+8YxcDlGcxMpfHi33mfm46ksKGtATXLK3P6hEtKQtiweQXCpcyE5Gs+GHi3YPcW2QbrKJu55GX6StkSfF9kW2yU++gxUGW99Hr+rAWRn1C/lQ0EbdwF1G6S3BBlAMq84+Xy8Epe58Xa/ruYoAhYIS8Kda3JBJtrikSoRMMdG+pQEtay3gvul+9r7fo6QZAf/0wbMg65kyvacN/9rTjxwRXcc18LJseT+PD9fgAaHn+iDfse2wBAw77H1uPpv3gbu/auwaOf2oSDB7oFMT/+RBsSMQMfHr6MD9/vx77HNuLdN7qx9+H1OP3RIHY9sBYrVy0V13T6xBB27Fqdde4VlaWii27j5hVIJEzs2LUa69tY6NCl8xNo27oCgBu3kAPl5WG0bV2Z+83ZurcinWwCcdMe+KYoB8A677JHuRfKWuBRm+wmwFuWH8p9HnmQKxsjVzQk2br0WkXBbW9p5CqL8/1REsTigRlL0dlnXyYzlj/e8FoxV2uV+Mz+TkrEdXr15XZKSZppvsd6GVyDNXRLOBmSScOTOw72UVfnKCXiBhmu3vrct44I3ZXrvCNDUUrEdfGobxoWXe6JUCpp0PhozNNn93eSoVt09GAfTUUSZFm22C+XRmZzcMjv8f9OJgzSdcvVnufPxueLg4wNFpYUeMNDlu2s8ALWfC9y5XYyeM0j4jXb8unhtxKgJIhbCxef+zmO/fF3AGi4849+/bocYy7xjxzvvXkJH77fjzs2NuCT/2IL3v2lJ1XEYwai0zoeePQOPP4rbQiH/ZWzZTmYiqTwxd+8DxfPj+OBR9Zj/aZ6HDrQLfbx2Gfa8J/+45v41Oe24p6PteB8xyj+9Vc+BmjApXPj+OS/2Ixj7/fjl/98AX/6v39CPOqf+HAA59pH8aXf2omTHw7gkU9uwu/9yUPYvqMJmQxhx+7VOPnBFdy3Zw3eeeMiYlED99zXjJ6Lk0jETSEzBIOF5FbldRvqcbmH/XcmQ9jQ1oDl9VV5A4ke/XQbxoZjWNVcI5o8ZoWYoRbyIiulqhHQgJEjXnBPIBGsmPS2eR/dnquql9qfBYLz7uYRi7WyVgR8k6Ltq58FoKHtq09c92PNJcHs0U+3Yd9jG3H47W6s3VCHhx/fCE3T8PAnNuL0sQHcfd9qTI4n0LByKcJLPQLW0xbe/eUlPPDIerSfHMJ9e9bgxIcD2LmnFWvuqAOg4eFPbAA04P4H1+G++1u9qEgwYm7bthKhUAg7drdiZjqNUImGigr2v/iO3a2oa1gi6cXAx+5vxdN/8Tbu37cO99zXglTKQjxm4PEnNuNC5zjWbqhHy5rl6Dg1jHt2tkDTIDRty3Jw+vggkkkTDz2+EYCGNXfUudnHTA4Jl5ZA04AvfXVnViARk0E24Fz7KOpXLEV5sZyQi8zkzITqVpEXgdr1iyIRLBeha+EKEdojUH+nO+D0odnzfueKRfA95ESusjjfHyVB3J4o2P2V4/Gab//6TzuZL7Y3QnraZP7atEkHXrtARw/2iX10dY76PiPb3ridyzAsOvRWN/X3RshxHIpGU5RKMtdCPKZL3W3s8b/7wjgdfS/bBiafMzunMTJNy/dZ02DSgWlaNDnOZInuixPCdmeaNnV3jbN/v9fr8ycXg3TKpK5zY973un/uTS6eW8IIuCjMwNQM45rlhHyOi5sJC+0dhsqCULha8CGWQUdDvvwDsf2nNmHJkjKsbKzG4EAU69saoIU0tK6txY7dq2HbDq70TeHwO7146PGN+NJv7cSjn9qErs4xkQXx7hsX8Z2nD+PkBwPYuXcNzneMwjQcXOmdRqgkhDs21qOsvAQVFWFxPofe6kFpWRj37lot9plKmnjj1XOAxlwbQwMzME0HU5EkAA3v/tL7bF93BI5NiEyk8MdP/v9woWMMd2yow4mjV/Cdpw+j69w4Wlpr8dbrXbjz3iacOjYA23Z834FlOfjgUF/OTIuKylK0bV3pfU+fvIpkOHcxDSNHWYXZ/CCbFqFpvrwILVx27QMog5kUNyEW0yBOH3Kxcr4/qgK+tXCtOQ/yIh2vVHl1aOgWWRarJI8e9KrElOuBTSYM0tNsYY5ta9P4aIzaTw7SS8+fFN7idMqko+/1BhoYOunShXGxSJeI63T0vV5KSe3Gk+MJsm2HiIhGhqI+/65l2WRbNnV1jrJq/D1/d9pz3zoiKvHuC+N+n+97vczfK1WvlmlTKul9h7ybLpUwRFdcoe+bLR7O7ecQrOjkNuF5X0S7CTvPFhugGjFuHcyXA2IuzRKzQW6xTcR1OvJuD01PpfyRjq47gmc4TEeSFIt6xBdsBebNE/4sCRbCw0l7KpIQjoaj7/WSbTs0NhyVmjtYN56e9vbbcXLIy4ZImoJY0ymTOk4NU39vhKLTaeo4NUyO41DHqSF2UzjYS+0nh2hkWHZY6MJFwZFKGnTk3Z4sws33fc/Hz+FGk6QnSxhFSRS3goxxLchHwEqCuEpY8TQ6/+srsOLpG35s7oC4+Nxr17SffNLC1eC+PWtwrn0E8ZiBjlPD2Ll3DapryvDwJzbiX3/5Yzj8NvPkHn67F1/8zfvwyCc2IhbVceTdXrz4dyfQfXESmhZCxsmg5+IkbCuDeIxFM7735iV85+nDOP3REO7ftxY/+eFJ2HYGb73WhbKyMHbsbsXv/ck+3HlvE46/34/6lUsxHUlh6MoMPny/H6eOD4KIXGkhg7HRuJAcDh7oRjJh4r69a3D6oyHcsbEOq5prMDEWx4bNDXjzny9g4+YVaF1bi3t3rsaKxqWob6gS44tAwMljA9i5t1VEaWYyhNKyEk+iebO74Pc9l59DvrjOG/6IzWWJxGBOicIXDylvfxPLGNcDygVxlbgRNrB8KMYBYcXTuPjcz9H21c+itLoy5zbcZmYYNt549dycRuwEUVpagnt3rcbMdBo7drfCtgnvvn4RH//UJiyrq8Qj673GDctycPqjQZxrH8Vv/M+70LKmFhvbGnDg5xew77ENOH70CkKhEB5/og2ANyxz+45mlJeHsO/jG0TXGrN7rcCWO1ehoiKMHbtWI52ysLy+Cpd7Ivh3/+cnUVKi4cBrXaIp456dLahdXglN85o3fvN370ddfSVzRTy4Dg9/YgMOugQqd8bdv28tMhlmedt81yqc+GAA23c0g4h8HXm7963F1u2NyGQIDz2+wfd95/s5FINrHek0b+BujKWr3YnIBZwZrY/cFOOBFgS5yuJ8f5QE4YHJAK9c10aIa8HZZ1+m72uP0dlnX5l126t9BM73iB1c4U/EDbJthwXgnBqiREyndMoUskQwoIblNxiUShrCQTE+GiM9bdKxI5dpKpIUuQ2JuE562qREQhcyApMWDCFvsNQzrylj4PIUdZwcIsuySU+zho9ETGf7fJUloxmGP5/i6KE+lhHxXq+QUY4e7KWpSIIOvHaB2k8OUjJp+BpMTNOikaGZghrvXHX4q2mO4bhWGWAunxfb5oifvB0B1Ygxvyitrrzhle9cMBef8NXOacvZUgzmclizbjmgaXj48Y0oCWt4858v4JFPbcKWO1fiwGsXUVpWAtty8ML3T2DZ8io88slN0ELsHGam0ygJhzA1mUIyYQKahhMfDuDRT25CRUUYVVVlgAbcs3M1yivCGB6I4nzHKMKlJbjSN4WhgSgScRM9Fyfw4t+dQG1dFe7d1YL1mxpQUqKhrmEJVjRWY3QohubWZXj8iTacOMoq2Xt2tqC0rAQHft6FY0f68cWvfAzhUg279q7B0JUZ/PLnFxCd0fHF37wPa9fXgTIEy3SwcctKhMP5my146/Snf3Vrzu9wWV0V7r2vxee3zuW/LlQtz+rXvlYv7Bw+P+cBmrcrcrFyvj+3YwV8NQteN6JN+FogtwvPxcMqR0x6//ZPpuBB6R2nh4VvViy87e8k27b9i2rurDXuB04lDXruW0colTS8PN+EIbzDetokx3FoZChK46Mxes11QqSSJiUThnBidJwa8h3Hkjy93DEhtwmbJltIC07USKVMGhuOkum6ORJxQ1xroQkaPGGNLwSySt3Kqnj5d2CadtaTyFyfTGbb/loX6ub6eeWe8ADlgrg6zOVR3oylaPRw+5w+sxCQc3J57m2xn5MdDaZh0YWzLLuhv49NnuA5Dz5CcWUFTtTxqM4e/13Hg2lYHpHtP0fjozHq7434Ps+zGWQCMw3279fdcPWgE+PowV6amUr5XAkiU+K9Xhofjfn2bxgWjQxHiYgR6EvPnxSOiWD0pmGw7N/gBA35/PzXwOIrZZKcjiR9MZnFjlXKh2uRJxSuLxQBXyXmovWeffZl+tner5E+FVuU+rAZS1HPj9+SKldjzhVw17kxj5xODVM6bVIqaYpKL5kwBLlyDTWVZOE4rIplPlrZS3v0YF8Wkfl1W50OvHbB1zH3i/3nRIWtp03WqWZ4WvLr+ztFN5s8keOb33iNujpHRejO0UN9ZOgWvfpyu8+2xsnPcPXbYJceP7d0mp2vYbARR/L58UCers4xYavj18kzh5OJ/Poon7CRSuaaiTe/E6AVri8UAd8AcLK2EovzkYtX5j0/fnv2jV3k+uUNVmZdnaOign39p500PhrzkV1n+7AvFa3j5JBL3IyMdN2iWDTtC1nv7hr3eYKPHmREaRgWtZ8cJMOwqOPUkNcMYdksrN1NTkslTZqZSlH3hXHS03K6mSGux7YdQW7y2KKjh/rETWJyPCHINumGrBN5TwNdnewJIpVkhJpKecM+208OZoW1H3jtAo2PxrxZdIE2ZL5gp7s+5/6+CBUjTRQi2fn0eytcHRQB3wK4Vm35am4QucbqyL/QlmVLjgZW9Zkm74Drcx/Fp3xVJGtq6KOBy1M0MhwNNFowEmEEO0y27VAyYdBUJCE0YV33CPVyD3NJ2LZDlmlRKmnQyNAM/eAHz1Nz0x0U0kK0fn0b/dkf/+esDrbx0ZjvWhzHocmJhOSAYFW0ZdnU3xthTgtJguCkbZo2dZwcovaTQzRweYosyxbNG3JFzgh1yrd/XgHLevlz3zriu1EE4ztzSQ2zjnRS0sSCQhHwLYCgtmwldBo93D7nirsYIvdVbof6sipg/gvd3TVOA5enKBZNU1/3JEWjaZ8V7NWX26m/NyLahFm3maercq3YR1Y/7STTYMQ+MhSleEwX8gNf2GI6r+EL4WHddDb98AfPU23NKvrUA/+OfuNz36dPPfDvqHrpSvo//sOzIsCHn1si7pEorz5TSZOOvNvj07uTSUNU4ETebLeXnj8p2pVlG1w6ZYqxRz4ilc5zeiolgoDkvOPxsficq1ZFsosb+QhY2dAWGQo1UAStZY5pYuKD86jdtg7hJcV3QBXTRFLI8F9RWYrHPtOGrs4xbNq6EiCCaTpoWr0MsZk0zp0ZkZoeVqOppQalpSV47Fc2o6tzDFu3N+LAzy8wi1g9s6Cd/mgI9+5sAQA88Mh6nDjGoihLSjS8/04PPny/H3/yHx7HHRvrcfjtHrz4dyegaRo2bG7A6eODbl6whq3bV+Gb3/y/sPuu/wmNK9jkisYV27D37t/C3//oO/jz/+1ruGNjPQDgE09sRklJCNt3tODt17uw77ENGBqIYqB/Gjv3rkH9iqWig4/n+96xqQHTU0lMTabw6Kc2ofvCBNZtrMeb/3wB8ZiBmWl3PBGAz/wqO/4nPrsFE2MJnPloUHynj32mDR8e6sNjv7IZ77150TfeqbS0ZFZrYNBydjXZzQqLALlYOd8fVQHPDrm6tFLGnCtUXuV2PP0S2XrhauZq3RbFLCzOVlF1nGKP3JPjCbHiz7XSlFQ186pPdkV0nBxyH7n7RJZCLJqmgf4pN1eBVZKppCF01Nd/6umi8oKdl+vA7HCJmE6aFqLf+Nz36cuff178+Y3PfZ80LSQsca/901kaH42T4zi+JhBDqlJTKUPsO5lgFXB31wRNue6F4Ph6rwLOdjLIjR5ccuELkLncD7wqzwel695cgMqCuDYUm/3Aq8uB1z5AxrQw8cF5OKZZ9HHavvpZ7H7697DhNz6B/p8enn3bZ35fVMR20oAxHfedZ67z5k0k+VqUAc/wHzT08yyCjZtXIBk3UFtXidMfDcI0HRx+uwc//sFJHHyzG3v2rRMDN1/4/gmccKdQ/On//jg2blmBt1/vwt33NeMnPzyJd964hMqqMOpXLMXJDwdw3541KCsvwcED3bhwdhynjw8iHjNw6sMBEBHKy0tw/761uHRhHGOjcViWgzs21uHpv3gbh97uwR13bMR45KLvvMcjF1G/fDXLovjKfXj0023ouTgB03Dw6Kc24Uu/xWIhTx4bEPkNA33TAIBPfHYzSsIhvP3GRbS0LkPX2TE4DsEwbGgARodjCJeGWHbEzy9g6/ZV4nvjw0sPvd2DsvISfOKJzQiXhnD3x1rwxd/8GLbvaM76rnn2xdu/8F+DjPnM8VBYQORi5Xx/bucKuNhqk1eXtm7OuULlNjFbN2j82PlZK+AgIme6qeOpn/iOmesc8mnAs2nDcsvw6/s72aLTlWl/9ec2VowMRYXVy9+eG2w7Zs0XjuP4Fsj6eyO+xTnZhzsdSVIqZbj2N8PX1JFOmfT8889T3fImnwZct7yJvvHH/9l1P9iiAn3tn86KkHcir/o0dIue+9YR5t+1HJ8+/dLzJ0VLMteieWA717f9uq9XQaekap4vJAah9NxbD1CLcNeGq8l+YIT6dtFE2vPjtwRZcgIPHs9KGWQl0jRysJ2sRFo6t5fJSqTJmI77zpMt1HX4ZBDZjsY/W8wNgzc6yNm4srRw9BDrVPPnNFiCiEeGotRxashnSbNtFveop00f+b36crvIgOATKjhhdZwaItOwhYXsuW8doelIkmzbIV1nXts/++P/TOvvaKOQFqK1rRvp//jfnhWRkt7CndfFF42y76u7a1ycP8+EGOifEq4Ffo5+R4UnsfhuMK48wLsDuzq9jIzX3cYMGZy4mX/ZFjcWhZsfioCvA4pxExTjVPD2kxSkKJOxjMTwJOlTMep46iekT8WIiGj0cDv9bO/XchKnldCzztGMJZkdLaX7yNiYSRS8yXBHhG07Ps8sr9iSCYPOtY/4O+06R6m/b4r6eyM0cNnVeN/rFVa0rs5Rsfo/PZXyOSh4eHsqaQqyTSVNSsR0nyYs+5J5KA+vpHm3GdeNkz5SNYRljB9XvqEwNwbLKOY3m1SKBQsx650U1iNlEqeShhi/ZFkemeo6s8mxwB/T1wVHlCfMSGm8twQUAV8HFCMxyGQZvTSQk9zEfp55mRy3KmLEmU2GtmX7jssrV30q5iN5Tur6VEyQs60b1PH0S2Ql0jRzcYAOPfmU6NrTp2J06MmnaPRwBzuObtLgm8fzGvzlx2S+IGW4rcGc7BJxnVJu8wK3n1mWW7m+ysjwuW8dEUHqetr0VZW8cpyKJKm/NyKC3Pnribie1bLc1TkqFgG5TzidYvkRhmEJqcS2bXIcR3T18ar16MFeSiVlW1gvdXWOCjIcGYoKkuZV7chQVDSNeGTPPL7BLja+XSLmeYqD36louQ56f/P9HFSX26KHIuAiMZdmBzOWosE3PyLHyr9aLZPlVEdvTrI2Yyk6+wyrgI1oYtbjG9EEdTzzEhnRRN5KWT7u6OEOMmMpmjzVTT/b+zXmsDAtX1MGJ3wroZMZS1HH0y+RGU8VVYkFK7dvfuM16u+dokSCZT6YpkXdXZ5Xluco8FZc3rjhVaIsEtI0WfXIvbt8jBEfpnn0YC8lYrqoRJMJg775jddYdexKIXz8EW9J5sE9sqQgOy3iMZ0Mw2skSSUNoePyGwq/Fi6zPPetI4J0TcPy3UT6eyO+EUuFJIhCuJ7TNBSuPxQBF4m5L5wlGVnFkjnfN6bj1PH0S2RMxyk9MZNXinAsmyZP+RfRclW3vDK1UjpZKZ3JCS55+8/Lr1lbKUPaV7qo76DnxbeKWhDKVbnxaphLBfJCWn9vxKs43Zxd/h4fA8RJ7vX9/jFGlmWLBT7TsKSW5zGyLFskmFnuzDeWwnaOYtE0JeI6XTg76mudZsFBXlKaaVj+Nui0Nybpm994zRt7NBJ1cxoMn7Z79GAfywXe783Kk9u25e8zuGBXCPl+DmrB7uaAIuAACjsBXnH12LdmrYQ7nn5J+HZzwVsES8+6Pyuh+4J8eHXb8fRLQr7oePolSo1NUc+Lb5FtWmQZFiWGJsnSs0NdHMt29V5PipBzIPza81tkxpI01dmXl9SLASdIeTEqOHZe9vIGNVdDt2gqkgjIESxNLZ0yBZGnkgbpaUuQXTLBuuJESFDKy3jQdYtSCcNtU466MoghKm2epCYqdCmAh1eW/D1fpsXpYX8056vnREXMA3+CC3IcQelDVbC3NhQBB5DPntXz47fIsey8j/YyrJQxawXMMfjmcfrZ3q/R6OEOil4aINuwyEoZLuHmlhz4zUCfipFteC4F3qTh/3ySul84IM7DjKVo5KA/GjNyppusRJr0qZgvNrPj6Zfo+J9/j3pefIuMmQTbT5zJK+Ja+WJiKn96l7wYJkdDigrYrWYnJxLU3xuhA69doJGhqCBDvkD23LeO+IZwcpIcGYp6ckenJ3dwsmOknU3qpskygJ/71hGXsNk5To4nKOWG9/CISl7VBhfY2IKa34aXC1yuSCUN6jg15Ju2HPyu5AVM2XI3n1Aa8eKAIuAActnKsu1ZhW1nZ599mQ49+RTF+kZopiv3Alu2RcytOF98i8x4iiZPXcrrYCAiivWN0KEnn8p5TqOH24VkwUm04+mXhLshVzTm6OF26v7RATr37f2u3syr/bfJNkzq+fFbdPzPv0fdLxwgK6WTbVgUOdNN+lSMBt445vuFHuif8umYPO2L27yOHurzdXOZpk0dp4dFXCUn52TCoMnxuFiIO3qwj0zDIsu0yLYdchyH+nsjUkjNOc9RsN9bCLzcEyHLsj35QspXYAuF/lFJtu3395omI/muTi/jeDqSFDLGzFTSd5MhKkxwwe+Ab8urZu4bll0l810JK414cUARcBGYq9dXrlDzkSgnwljfiCD47hcO0NjRTkHIxkwiZ2UpOxlyacdWQpd8v14FPPZBp7CamYkU2YZHDrmqdtu0KHppgCzdfe8Z9p6lM0I+9+39TKKIp+j1n57NqiyDZMQr1lwQ0oA05aK/L8LSzCybLMvyOQf4AtnRg71uMplFx49cpqPv9QpttrN92IuMdPOIeYsys4WZdOitbl+AeippUm/3hI9A2bG5B9j0LbTpukWJhCFasDtODRMR+QidiNzozNxtxHKgvRwu1N83lZV4Nl9QGvHiwG1LwPM1HsiX8eB6a4MOglzHsNIGGdEEDb55XPL5JmnkkCQPPPNyTidFMV1sQWlg8M3jdOjJp8jSDYqc6SYznsoi93wLjVZKF5q2nLjGmkkM6n7hACWjKd8j+0vPn8yKdhTknOORmmufRw/2Ude5sSzyNnTLly3cfnKIjr7nyRnJpCEWt/jnglY022ZWN+7d7Tg1JHRdecEuFk2zVLJIUiza8WMHdev+vikiIjGYMxjMnoizAaLJhEGJhE6v57GMyU4R3sl3rRKBkhkWP25bAp6v8UB+W1f7HNqSXyZjOk56JErdLxwgx7IC8kC2fkvEqlLuITbj2TLJ2WdfIceyPcJ85mWhCxszCep4+iXSI1GKnOnOc16viMCgyJluciybSQ2RqKiO5UXD8WPnSI/EaPCXxxm5uvqlnGHr01MP9tGB1y6I5gaO4CM8h+ci6PW5CPhsOS4VsOaOMSF9HD3YS8eOXPaRkFwxd3eNi9FC3B9smZavuk3EdLGgxitkb/yRf3JId9e4aCaRHRKppCGkCuEb3p/7sZ9Xpb5uumuQCJTMsPhx2xLwfI2Pl6tcZuny7zNXpS2T5cih9qyOMyuhk2PZ1P3CgSxCj14aICOaoORoxCcZMH33FdeDfJxSY1Mu2cZo/Nh5cVw/wQeaOVxd1zYtMqbjwgHBbxa2YdHgm8d958Q9zyyn4pyvYucLT5ZpkaFbdOTdHlERxqKsUuaQrWGcgGSyS6dM4VSwbW45k8mQeXFNd9yQabKwdF5Zcw33m994TTRj8NQyy2KuCbm65d16tu3QQP+Ub/tckLXlI+/2iBly/PVkwqB02hRV8WyYD4lAyQyLH7ctAV8rZGK1DSuvlSy/XPAKGdNxshJpoede/OEboo04MTDGKtanfkJGNOGzhlkpnRzbppGD7XToyadE/gPvVjNmEsyOphsUOdsrOtxsw6TImW6/a8Jte7UNi3pefIv0qTilRqfo7LMvi8W7IOHmunH1/PgtRvquTmxEExQ50y0WrlJJ9pjN24S5RjzQP+WrOlNJJh1wLzBHx6khOn7kMqXT3rbdFyeIiLzJFDGd2k8OCkdDIm6IBS9OoOmUSbZrN7twllWoU5EEvfZPZ6Wgda+67Tg55LOfiZhIaUKHPPONW+Y4UcvEbZqW+A5kKKng9oUi4CKQr4rl9rH0xAyd/ssfUaxvxN1erkyzq2IiL6eByQ82Wbrp/5xhMVI91O6zmp199hWyDUvqjPO8ulzTtXSTrJRO48fOk+M4Ps+vldJZx5wrRVhJXVTE6YkZGnzzI+HM4Lo0X1C0EjpZukmxvhEyEynfAqCtmz7ZY/LUJTr37f2USvABnNkLcJPjzNfrpaB1CieEsGL5KmGv+UIehEnkkbDccSZ3lcmarOEOBuX/5jPjuMTAxxhxjXlkKCq293mB958jy+3Ik+1pMortGPQtuikyvm2woAQ8Xwth1xu5qlivOYJZyWzDFFquTETy9pwoxaP9My+TEU0QEfl0W968wZ0GvNmCE7kcL8ltZrxDjsVWuhGPgdyHjqd+4mU6GBZZukEjB5n9jPt9WSsyu7nMXBwgy62auZvDSukiw0LWkbnGzJ0XViLtVtimJy8EhkV2dY76fMH5yMtvE2NZEIm4QR0nhwTBBqtS2UMbnPkWi6b9JOo2XMg3iGCDiKFbND4aF5kOnLynIgk68m4PHT9ymaYi2Z7vYmQAeSio3N2ncOtjQQl4vhbCrjfyDa08+4ykqT7zMqXGpjyr1zNydcpI89y391PH0y/Rz/Z+jcxYkkYPedGR3A0h28D8JM904fFj5wLxkp6DIto7LLTfYIzk6OEO0qdigvCJGMGbiZS/8nYrca/69dLYrITuI2Pb9B6luffZSrFtuG948M2PfL5cDt4qnIjrWb5gDjFJw01A4/uYiiRIdx/zRYPHe17qGCdlHtQTTGYTGQ1u+pjfS+wfeMnlgpTbMBKP6Vn6cdCWdjXwdfflcIHwc+I3ivk4psLCYxFUwNe+EHaj4LOcuUTl6yp75mVyLO+XQe6aGz3cTsZMgmzDpOilgaybj5VgGQ76VIwsKSfYt2B3sJ1SY1OiE230cLtIKps81U1mLEmRs705YiSTZFtua3JKkg0Mi6y0QR3PeDpv5HS3uAFwEuVtynJFzapcf8ra6OEOQcQyqY990Ok7LpGnjQajF4OVbFfnGBmuLEBEIoqSL+bxqpg7EDhRyk4MmaDk8e6xaFqE5RhGdpsxPx+f9cyVScZHY6ILzrdwd24s57XMhnyVsvz00N8boeh0OnuxUDqmws0FpQHPAcH23UNPPkXpiRl/TsSLbwkC06diTGuVGjJGD7eTGXOrTim7l8hNM3Nf424CbkWzdYOG3zlFg7887nuPk9yhJ5+ijqdfIse2aebSIJmJFA2/c4rMRNq1ikV9OQ6MMNtp8M3jpEc829vpv/yRtODmr8jl6x9+51TOJxeZiPlNiUskHJ6tK7/sECRBeVKyLB384tVzlEqZ1H1hPKuDjWcqTE95N3jelRckVnlyh3xOcpMEP5Z3E9BpZFgOcTd8ZF9I/81X2ebahu+XtzznWiycD6jFwBuP25qA56JBy4E43L0Q9Oh2v3jAl+tgJdIiZ6Hnx2+TldIFUXJHgmVaZOsG9fz4LR9Rx6+Mkq2bFDnbS0Y06RJ3UlTJZ59l+jHrRnubRg667yd5M4jX4mzr/iqXiHyV6tgHnaKhgssQfBv5M1z20KdiWZ10ub9bWSLxvuNg6pht26KRIRcJioS0PO8bBnMXWBZbTOPJZzxRjTd+GAZbfJPzIpKSR1nWlDk4+es6czucax/23QRM087Z3ae7C31+77BHbsGsYnnUfdY2gZuRLI3MJ5Rv+MbjtibguWjQvOIdPdROkY5emrk4QPH+sUAwTVqQoz4Vo+jFAala9ZovrLRBM5cG3deTXpKZS6RWIk2OZdPAG8fINsys6Eo5mpJl+iYpMTxJluSWGD3cIRb1cuVFGNEExXqHqefHb9HAL475FgB56JBoW44lKTEwRrZl0cih9qxq3puuUVxSnLfodM5t9fUaKrzJyP5W5uAiHZcMgkTEZ6oZhkXjozFflgInOp7KdvRgn2sPs4XjIRiGPjIUpYHLnlUulTS8/06ZpLuVdPA8RHedKw8EyU1ukU6nTbpwdjRrmxvt41W+4RuP25qAi9Gg5YUwYzrObFw8qyGaENqmGUtR9NKAbwyQ0H1Ni84+45E9D8VxLFtUpmzhzKDEwJjv0T85FvFb0CxL2MjSEzM0eeoSRS8OUGp8mhzHISul08Abx8hKG2Qm+OJhmuIugVopnbkbEmkhSYwfO5+l2R7/8+/RwBvHWJfbm8cpPTEjuTi8av7ss6/Q5KluEdTDNWMvj2L2+Eo5Z9eybHq9iEf3ZNKgV19uz9mya9uOlGBmisU207Co/eQgpSQyTSUMH+nL1Sqvei3Tbz0bGY6Kyle2s2WdZ9bkCm/WHK/a+X/390XmlQCVnHBz4LYm4GIgJ4udffYVSg5P+qpFK81+8Xp+/BalJ2ZE9WtEE551K2148kU0Sd0/Yh1ug29+5HNMJIYmyLEdfzVq21nji/TpuFjMswyT5f/qhpiEIbsXeFebLEv4dGnXCjfV2UeOZVNyxN9hZ1sWObYtbiDcrSF8xbrhky9YV5y/4YO3R+eTe3gOMM/ztW1HTBMOwtfw4E7P4MQ4PhrzZUHwqll4iw8yh4RM8Lw9+Oh7vXTpwjiZhl9n5Qt6ejo3OQZDdwqBV+Cv/zR3ZGUQ10KiSk64OaAIeBYEw9DlhgkRgG5YrBFB6Kwvk5VM+7ITuDbMsxyEXzZtiMYG22TNFzIBxi6PkJXSpeaHNA2/c4qMGX+rMNd5/d1rL1Osb0TcQOSsX76QyCdhWK7UEdyGhwbpUzE2Zsl2vED4Z9gNSJZQOGzDyrpxcDmEg1+nHagweccanwwhgxNrLJqm/r6IbyGOtTrrwtf70vMn6ci7PTQ+Fhd+46BTQra39fdNie2CoTv5xgTNpWrNl3eR7/1rIVElJ9wcuO0JeK7NILZhseCZeIq6XzggWm7ZvrxqdvCXx8nWDbIMy2s9jiaFT9Y2LTLiSZ+vlp/LoSefosTQJKUmZkifjrOut2dedmWAtyk1MUOjh9uZr9gl/e4XDpAeiYlKVG6I4ItnrKXZ62wz4ykmIzzzMqVGIjktZMmRCI0cPEMXf/hGli+Yp7md+/Z+mjzVLdqaObypH7pIT/NuGN4NSx5xJHe6tZ8c8uuh+zvJNC1pcoVHVl4l3EmT43FBZqmUKbIhZJ3ZcRyKR3U6fuQy9fdFxDnzoB95Okc+EuPZw7IGPFfrmRxRKTs4xL4Uid7SuO0JOJhmNhsRi/jIF99iC2Qz3rDMwTePi+aDsaOdotqzEjpFLw2QYzs0fuwcnfv2flcykKQCwyTbYmTtJyrDl93AK3ChSbsjjWzDpPiVUbJ0g4XLjEREJ11ieJJGDp6hn+39GkXOdPt16kPMPTHwy2OsOeRwBw2+eZwGfnGMyQnuwp6VNoQM0fHUTyjWN0K6e/zRw+1MD88z1y7X953V5uy2UcvNFR2nh33V4De/8RqNj8VpZCiaNbJHbrQwjdxpYpzwUtLf+cgyuIiWC0E3B/9c1nnlOQbPrwjOx1OEe/vgtifgYsLTZdiGJRab4lfG/I/rUpvuzMUBsfgkutzcoBpuTet+4YCvk07uUuMkOfDGMTKi7mSKHPYw27TIjKd8EZaDbx4X5MyzHbjs4e+iYzcbLikMvHHMvQnImRSmO3njLT9humQrywzyk0C+cUy5pncU873L7bpMOjB91WkwrSxf9WjbDv1if6d/7loO/baY6tMwWMobD+jJ9bl8RB7MtigkM1iOSVfiZ8lyzIKvKdx8uO0JmMOLlfSsVHLAejCNLHK6W/Lk8jhK9shtRBNkRBMiBtKxbJ8LYuTgGUZiST1rPhuRNK4oqYuYR1nekEcGRU530+SpS77Usr5/PEiTpy6RmWAkF700QJGOXjIl0h852M5CgKScYCvJuvFkz/DIwXahTxMRObZD+kxcVKxyt5xtmD5nx9lnXqbE0GRBF4QsU8yGQproXPRSVgkzj3Cx8ZD59jOb3BC8cRAR2Y6/oURuPc6FK/Gz9M7QD+hKvJOm9VGyHdv3msLNi9uCgOei8wbbh7mnVh4bxGUHYzpOff94kGYuDZKVMigxNOnzC/NZanIFKlfaPCJSJlQiL2mNE6MZT/nsaue+vZ8t6FkW2aZFz3//B7Rp9ToKQaO21jvoh997znMppPx2MB6Swx0LIwfb6eIP3yDbsslK6yJL+Owz7POHnnzK523mkocxHc+yzI0fO+8GB3mVsj4dp+4XDrg/B6+rz/vZFD9puVBVquu5ox7F53IQpWXZ1N8XmVNTg6dFZ8sc+arS4HaR9CAlkqmitWK2304yHZ1OjP+cRpO9ZDkWTeujZDkqB+Jmxm1BwHNpuPBNhXCrYq8CfsWnyZ599hVKDE2yBTU3u9dKpCVdmC1icULlVSlfkHMsi6Y6+1iITdpgVbVrK5u5OOAjfXlhjckSrMr+q3/zB9RYuYz+FDvob/Eo/Sl20KrSpfTb2Ma02t4RX3UcHxgj2zBp8JfHmW6rG0zGkBcQXe3XSukU6/Vm1nU89RMaOdguWovHjnZ6lf0zTK/mlTGXFri/mYho4I1jYvGS3wyDCXDFIriAVagazWUVK6Z6zbWNaF0OTC4m8irV0WRv9n7c7UaTPWQ5JkX1cbIdW/y7GFiORVfinWQ5lo/s57IPhcWFm5qAi61s5yP0x0oxu5ilG74kMjOR8g3W9OUgSOE28mKTlTao+0fMQeFYNvP2TsWo+0cHfFoxC2tn7gXLZME5PT9+S4T6nH32ZWrBEvpT7KDva4+JP3+KHXTH8kavcUSE8jAbnW2YlJqYYY0Zbuawz7Nr28L1kK39psUCGm/gOPvMy27DBusKDFr3vJ+DZ9/j2xbSizlyEaEcYxmsRvm/+faJuE5H3u0ho0BOQ650sewK16JUSs9bhTMy7M1bCY8me3yywbXICN5nz1JP9CMlRdykuKkJeL7iLIshcnmxafidU2REE1nEyd0InPC43MBD1+MDYyJvl0c3coLjDgo5S9hxHJq5OCA67uRKduJEFxkzCQpBo7/Foz4C/ls8SiFNY+fYO0xmIk2R092uz1gXi4BcVuAyA2/QiA+Mi8D372uPUfePDlByeJIcyyZ9Ok6Rjl5BoLZpudfxNhnTcfFz8V9fyv/zesZzd1yt9isH7wSr0eAod8OwxJSMQotlwXSxXBXuifGf07Q+WvB8ZXKUwaUETszBf/u3K7zAJn+Wk77CzYebmoBzVbZXE/I+W+A6s4Z52jCvRG3LEo/a48fOs9dffEuMAOItw6xJgWUusDbdtO+97hcOkG2YTEt2iZHrpWYsSTNdA97IH2kGXM+P36K2NXfkroDrGtlQTdtmGcXxFMWvjHmDOQMJbVYiTcnhSbEQFzkTrNx1YZsTzRsJXUzWmLk4QLYbxZkV05ljnJH8fc4GmQh5cwbPishVjeZLNZMr5OCI+HyJZp5MYPm02ELa67U6FBb7AptyYMwfbmoCzoWrqYr9yV1egLrcgswrNr4Nb1jgmRD+UJ23yErpQkvlFef4sfNkpXTmqZW8vaZLyGxfSXIcRwzkZO3IjtB+bd2ksQ86aeQgI/4f/M1/p1WlS30acGNlLf3Vv/kDKbc3LRpD5CqaBfmkyLEdsWDIXRZ8Fl16fIaspC7mxHEtePRwB426A0U9jZpVtPGBMYp09LLZdJJ9brbvnIiyKnT5Rsq72+TKNxcsx6KUFfORZKEKuRCCZDitj9KJ8Z/PCznmIzK5umW679WR3fUiysV+g7iZcMsR8Fz0XmH3kixV8tw1uWWYLyBNdfaRGWO6LyczWUPli05jH3QKTy0fkOlYNg2+eZwsvujl7lsOaO94+iWW5ytpo2aCWdzkhTLbtChymuUt/Da20R3LGymkabSxqZX+05f+QFo0O0Ojh9op2jPkq6INdx9mIiWqYt5OzN0fZ599hc59ez91v3DA5+TgHmN+DXz6hjxx2YgmRGOJVzVnyw38O+dNK2JeXQ5fdjpl5lz8IvLIxnZsMh2drsTPkuno4r3RZA/ZjrRgV2SHGauAewOygUdqtmNTJD0o9p1rm3yvF0Nk86ETF9Klrwb5pBOFueOWI+C5QCYNf/xi9sRfWbvs+fFbwjnQ8fRLQlIQi1G/PE4zXQOku3kNgvSiLBlNkFMiTY5tU+R0N4uZfPolMmYSZKWYMyHWO8Lyg5/6CSWHJ33VPe9gM+PShOWkTlZaJ2PGy+01oglfzsTkqUvMr2vbFDnTTSMHz/jmy1kpXSz+8ZZjWzfp7DNM1431jZBjWTT2Qaeww1lpPUt24EFFIjfC7Z4LItj555dGOgreSOXqkC9wxYxIFmnJ/5aJMvc+PaKS989JdjTZQz3RjyiSHvI5EPh2hTy68utJcyZL0sjfcHF1ZMc/q3zDixe3NQEHpzfIQTHB7WbTLm03WF3ucrMtb/ClPNQyOM1YXsCzDJPMeNJP3DMJsgwze8LGMy+zKcW9I2S40oFokY4myEykKXFljJG766wY//AcS1JzPch8SvLo4Q4yEynR9TZ2tJOilwbE9clZx8y9YYlYSyvN0tDOfXu/X9v+0QH3el/xXS/rDPQTa3B+XS5d30rovko3SKx+i5ZHWnJFrFsJKgR5AU23kj6ngVdJdgoyjqQHfecRMyJk2Kmc1abtWDSa7CHT0WkwcZ5iRkRIGtP6qCD3oI1tPqCq1sWJ25qAObwuuOImY+SrknkcpTEdZxqxO/BSzFGLp0QUpTyqh0+XYFkM7e4CV9rXtGClDG+hzK1QueeYh7VHLw2IRT05OIfrybyJJBhZaSV1cVxejXqvscf4yJluX8C77HUe+OUxbzFRTPh427XBsfOPnO4WvuCBXxzzLcwVevog8sh59HBHjsfqYhbFvKaF2TyzwWo2ZkRcmWHI9znbsXNWwJZj0GiyN6vS9rYx3PNgzRT8GJZtXpNMoHzBNyduawIuxjHhJ4j82/rjKF8RKWm+hbxAFCVPFLMNkyKnu31Wt8TAmBeI47YBWwldZEbYbsNG0L/Lx9TLi218AdHWDUH88vtyhgURicp98tQl13HhRVLK23v7N71sYzd3mD8JyN8zd0/wbeXM4HxPH97nX5EqYK+S4xVkMTpn0IebC/ICnuVYonr2ywIW2a48wW4GPWTYaRpN9uS1qeWSAPj5mo5+zTLB9fYFK+fD9cFtTcDFOCbOPvsynfv2fl+WQz7IwT7cuys3QXA4tkOWblB6coaMqBtdafjHyPN8X2+xy6+PJocnafKUn7SNaIJs3RAEJwZ82jb1/eNBSo1F3NB2L4mMh7jLGcHMqaGLpo/E8CQdevIpmukaIDORJks3czZaCL3XvQmcffblvN8zz0jOtZ+5oFidkxGqMYvv1iDHrUgHE+dpWh/N6f3lcoEsNUT18YIklUsC8CSHHlYFX3MFnN8XfKtb425W3NYEXOxIIrn6m40oRAvuUz9xq0Ddi2tMGVLV7WqiiRQ5FvPqymPkuWwQ7FIbOXjGXajTRTvy6OEOspJpv6ygG75gIDORJstgTRNptwsucqZbkkleEdJJ0BUxc2lAyhLOzm3wX9Pb5E3GMNz3s7vdbN0Uo4vmC4V0TiYN9JDtVrbiPALEzaWKpBkVpB2sgpn84EkNfH+8Mi5WAggu+EXSg2KBL992uffDzrNQNkS2Xj43MlYa8vVBPgIO4TZAaXUl7vyjX0dpdWXebcJLynHp+6/jzc/+ezTs2ox43zCseNq3jWNY6P3J27DiadR/bDMe+O4fYevXvoBlW9ei63s/w2sP/REufu/nsFNpXHzu5zj2x9/BxedeR+WqOmRMG+f/2z+h7q710EIaGna1ASENLZ/ciV1P/S7q7t2ATb/5Gez6L7+Dtq/+Cmq3rkVJVTn69x9Gz4/egj4+jdq71kELl6Dre3zfryEUDqN221qc//Z+XPzezxHvGQIsGxnDQs8/vIlM2sSybWsR7xmGFi7B1q99AVpJCJu+8mlc+rvXcfzr30XPPxzAms8/CGMyhsTlUQy89gHS4zMY+PkHvuuXr2n9v/44SqursPL+bbjwnVdhxdMY//Ac9MkoBl77EABgxdO48J39aH1iD8JLyq/pZ2hnLAwkOmFnLIRDpWhdug3hUGnWexF9EOdnDmE41YWEFYGTcQAAUXMUTVVt2Fr7EJqqNmIs1QMgAzPDfsbhUBlGU93oiX2EiD4IO2NhOHUBgIblZU0gchAzx91twxhOdeH8zCGMpC5lnYPv/5mMg5HURfTEPsJI6hLCoTBqylZiSbgONWUrfJ9JWFOYSPeLfQaRsCIYSV3C6cgvMJK6mHObpqo2bKjZhaaqTZjU+8Vxi0Xwu1W4zsjFyvn+3KwVcCHI+rCVMnytxewR39OGO57x8g0cyxZNFXKIjzEdFxowlwZsy9Nwg5Vu5Ew32bpB8StjbJCmO+b+7LMvswpYSjWzUrpYCOMeX/l9M5FiFfGh9izLGa/WZ7oGmLf4DLPEcb8xH94ZHJVExJ4OeAXtJawdF75gWSPOl2ec6/ueCwo9GgerPlaxWmTZcvXqr0JjRiSnj5jtw6Kg1upfhLN8vuHcTo2zwkERdEvYjk2WbeT07xZaaOQVuVyhyh18QahqdvEAeSrg8ELfABYavKqjDGHr//IF3PlHvw47qWPr/+sLaHxoO87/9X7ok1GkhiI4/vXvorKxDmv+xV6c/2//hI2/+Wn0vfQeAA13/tGv484/+nVkbAd9r7yL1Z/ahYbdW6GVhDD6zmm0ffWzADTU72hD3T0bAWho++oTKK2uhGPaGD9yFqt/5X4sWb0SF76zH8f/5LsANDTsbMPxr38XIMKK+7di1d67cOVnR7Dl9z+PULgEfS+/C30yiiv/fBRrfvVBwMmgfscmLN++HtA0bPiNT+DKq0fwwHf/CDWbVoMyGUDTULNpNUYPtWPz734OCGno+s6r6Hv5Paz5wj5c2X8Yx7/+XWiahi2//3nEegZhRpNIDkywCvfnH2CqvVdcA2UIbV/9FZSUl6L1iT248J392Px7n8eW3/s8Kpvq0frEnqzvm39nhWBnLIykLqKpajOaqtoAaGiq2iTedzKOqGz5eyWhEtRXrMZwqgtNVZtQX9EKw0kgYgyiJ/YRACCEMBoqWkXFC2hoXboNaTuO6tJ6dEePYf2y+wCwitJw0qgsWYoJ/TIm0v1orNqIkVQ3mqraEA6VIpNxfOfAK8+yUBXqK1Yjog+huWoLCAQrY2A01Y2mqk1oqtrMfsYVrRhOdfnOpdB3wd/nrzVWbQJAGEh0inMCvGpWYREjFyvn+3MzVsCzVVxmLJU1bJL7Y3tefCtg93olq+oLelkH32Rz5FiFaLDOugIJYMHj8wkbourlSWmuHszbnh3HoUhnr29bx7aZs8G0KDkW8YUAsUYOf+i8MeM2b7jNIv5GlZfFOdmGFdDHvcYNOaidyAvokdPesn8exS3GFfLL8orRsFNZWmqwWpa75jz7luFWk2xRju2TuyFY1eg4jniNd9glzGhWkwbfb8KMUsKM+q1oti7C1fliH6+sY0aEdCtJF6be9x03F3I9Acj7sh1r3lqnFeYfuF0X4fI9Bvf8+C3xqMwfneWcAk44uTIOCpGITDzJ0QhNdfQWtLYFO8p4s8PxP/8ea7awLLJ0L2dCBKG70kHPi2/5bGaenKJT94sHyHEX4byJyR2S0+Nlt9Mv5bOKDb75ETmOQ4mBsawBnNnX6/8ugu3bs+X/BtuHg+/lW0QKkk9wwS3oEBAeYdsk27FcN4Ml/L9EjPAHE+cpbcXF9jEjwuQKO53VOeeXHs6S49h0Yep9ihkRipuRgIWtN0DwRkDKCAw6DcgdwYxgWRIx7BSNJnvdxTklNyxG3LYEnIss/YljuSsxPuiSzz8rFsHhn5wU81nb5FE9ZiIlKmaZ+H3z2Dp6fePouffXmEn4mj+stEGHnnwqO98hmhDt0HJ8pGjVftHfvOFNvpibbltM/i8R5dRIOQrbzUxBZBem3hfbyKQdSQ/6NFWv0cIiw0rnJFauGV+Jn6ULU++T5ZhZlSuvNoOeZM8Cx61ujiDr7G45W9rW8m4Q7rlyW1wuZ4ZM6o7jqJjKmwC3LQHngq2bvgYFomypolgCIfIiLflQTnkhjzVheFUxJzgOX/COZVH00gDZlk22Yblty/4mjPTkjI8gWXKaQZZueOOQIlGaPNXNXotEaeyDTnJsR5xrsKoXC4jRBI0d7fQ1msR6h4vyUV8tglWkXM16VV+hjjavMuRNEnxfkfQgjSZ7shomIunBHMTK2osZobGbguwPFgt2dpoSZpR0K+mS5hg5ji0mXwT3Zzu2r5uOV9vysfMtCAbPT7eSBW9Y1wOqMWN+oAg4gGBlHCSZuZDO6OF26v7RASnz1/Ll/VopnUYPMY8wb9PlGDnkjfSxUro0APRlSk/MeJ1nOeap+aIsLfaL7di2Ow6JddIlRyOSLFK4guXkLDeEeLPiXiFjJj6rJHE18Ou5g1JlWEwrMSdr7zO8IuSP6cEAHMdxBLF6rgLDV9Vmuycs8W+5KuUVrunoFEkPSuRo+Kpr3Ur5zpF7iSPpIUH6wWrf73ow3DZmz9nBbyTX8p3P9nnVmDE/UAQ8C3JpmXPJjQhOsrAtNloo2IYb6x3J2bqrR6I08MYx0iMxn5SQK2PXO2dv+OVUZ593HtJgT1s3qPvFAznbgINVP28msUxLZFbwynjyNEtX4zGdV2MlKwTZPlbML73cmkzk14RTVoxiRqRgUpqcfMa606ycujEn8Uh6iCw7W46Y1kd9+02YUXIcJ0sqCF6X4zhZXXW8Sy7Xd8PO1aKUFSXdShTVbl0IxRKrsrLNDxQB3wDIpM0XvrgjgEsF3GVA5K+yeTawv9MsRZZh+cJyguCz3vgCXfcLB0iPxHzOCm+R0dNybcOijqdfop/t/RqNHu4Q5/OzvV9jC3hu6lnkTDdNnuoW+3IsK0u+mU8kzKjrOujNWlwT1+wLvJEXpOTIR0+aIPInpRlWmnQrkbWIJe+ftyEPxi+4UoJFU+nhrGpaJih/poSX1pbLD8zPWSZSpgHLi3M94m/T1nNW3rMRY75KVxHrjYUi4BsM7qSI9Y3Q+LFzZMzEs+xufHHNmI4L2YAvrjmWLch64I1jZKV0il4aIMuwRE6vzaMrecOH2wDC24NlZweRn/AjZ7pJj0SF9czWTbJSrK2ZL1Ky6ppFZ3b/iCWs8XH2uRYwfU0tCf2qqmRu5+KP61wTlcGrN7kazWVVY4tgnOy8Ra7cC2ueC2M02UPjqcuiAuY3AnnCsdecYZFuJcmwUln7TFpRoSvLLdKR9KB0XK8Bg1X0fncDP2YuvTqXRS9IuNzZETMic/o55NqXwtVDEXAezPVxei6Lc3zfPJ0sGIZuJlIin7fvHw+6U5i9/AjhaHA1ZD4tgx9fd7eXSfVne79Go4faRbJa9vm8IggycqY7pyNETAaRKnIW3mMQD1bPJY0EHSDXUiUX54Dglix/LKRcIfMKczTZQ5ZtCCnA7zAwKJIeIttdTJM/7+m4Rg7ZwJKI1ZYq4E5RxfLzki1vXnXOKvhgp57f2saPafi8wsGKP9/35ndbzC234lplDgUPioDzIN9iWz5iLtbfKjsteCXK7WKHnnyKzj7D0te4zYtP3PAf380Cno67s9uSvoW3xPCk57qYjrOQ9GdYsHuxyOUIme27yYcgwefS0As/EsuLasU5IPhClLzPYGXL3xMBOm5zBCc/TqpcZ+UEnbJiEoH3kmWbNJg4T7qVItuxWTOMb+GNVe+s8cOr4HNJEEzvNURCGv8cm6DhnwDCNeigVzrX3LrgzUmurj2rnpVTzsgffp8v9U1Vx8UiHwHf9q3IvEW47atP+F7P1zK7+cnP+v7Oh/6fHsKG3/gEAKD1iT0ora7Elt//AhzdwPJt69D21V/BwGsfYknrKtZ6/PXvQguFxLF4gBAAdP7XV3D8T/8GWkkJtvze55B+6nex+cnP4txf/xRbf//zaNjVBi2kIVQaRtNjOxAKlxR9/ayN+AlooVDWd7DxK58GORls/MqnitqXfM4AcrYa82CaYMvtSOqiaPMdSHShqaotq43WyTiY1PtRX9GKcKgUI6kuWBkdSXtGtBk3V20RbcGNVRtAILRUbUUGGUTNcdRXrAGQQdyaxNLSOkTNUdSUrYRhJ1Bb1oQJ/TIaKzeiqWoTRlKX0FTVhrvrPomashVu2+9GaCgBIYPh1EU0V23BcOqCOL6V0VFXvhpxa1K8VlvWhIaKtVnblYYq0VzVBgJgZQwQMogYg2iqasPKinWI6AM4P3MIG2p25WwpXlpahxWVa33t2XL78UCiU3zX62vuw9LS5QBYqI93fhqqS+tF63SwrTtfK3O+n6PCHJGLlfP9uRUr4HyYiwsiF3h4ObOWGVd1LDOWkrzFrHoefucUpSdn3EkWHb4qdebigK8t2L///J148kJcMJyIN4nMF/It/uTyvcrVK6/S5NZjy7Vx+ZsvhoTuqlsJujD1Po0me8hxHDKsNDmBKm8wfsFXlZqOTklzJutRPuiy8LTnHvJb4HibsywRGK6OnL2dnVM+OOtq0P7gHfk6eVU9GL+QV2KQv+uEG7vJvze/nJFfb/fv62zgXNQiXrGAkiBuHLLkhqvUQX2twbbjSz47/Zc/oslT3UKCkNPcCs1hy32u+f3Qc7ne+bClyb/YQYeAR3h+MogZERqMXxCLXKyDzetIkx/F/URoiEf/SHqQLky9z+QDyXHAJYRsl4Wf9PlCHZc2OKHz8+E3Ci+H2C81+K/dEFox395wtWh5jl2um1ahdmTveMG2Z38XXi4oP/C1QRFwkZgPMikU1jP3c8lNjvJ+HcvOGoCZ7UiQB2YWHs0018r/aki7kIYoNxnIFq9cEzG8Ktkgbj+TK9RpfZQi6UHxh1eCsiPCq7Ll1mDTZwtLmFExQYMvuolFNdugGWOMovq4OH+uI0/royKgh38uZSXIcRyfhssDe3Qr4VscZG3WzFHhP1dGlrzdmROvX+vNp43PnURVxXttUARcJIolk3xEzduS84f1yHPT5vZon8uBYMZSdPYZ1jUnSw/5xgMVc2085Swfoee+prmRdiEykB/vHcfxvRd8fJYXyYhINEPI1Z6XmevP7s1VPfIKM6qP+yrr8eRlX4Ua1cdz+np5V5vl8+0yBwQnR3ksEZcoeNWeK3eC3xAi6UHf9+H3QMuLe5bve/QTcm5JQ+H6QhFwkSiWTPIRNY9jjPWNFPxcx1M/yam7Fnd+L+esimXrWa7rKDQV2rPMmTmvbb7zIApVVLLey4lVtoZdjp4h2/Xf8qjIIKFZjkkJY0q8zvbl2cWuxM+Saes+/VTWXINdaqw6TQknRTDDgg/I5NGXhpWmaX2UhhOXfGPqLcekGWMsq4rPlTshX3/Q78xvKjP6uE+qkbvpZqta/Y0m2Wl0CvMHRcDzjHxEbSV0yc+bv1qUK+C5kFtwW9kXbJtWlhThHbMwwcvt0rmu7VoXJYtBsFLNV83pVlJUqZZj+CQH3h4sV5n8dVkGkCdJ8JCbC1PvU8qKudM0/J9ln/FPSH7+H56njVvuoFAoRG1bN9Dz//BDsh2bhhOXsqpTTqbyNQrpxOY5E/wGwGfO9frINDt9ze/ZNR2dBhPni5YY/DctVQVfTygCvoG4Wv9sPkmCE6g8+ogToRyIHjnTTVYyneWCCI4NyiedXG+CLQSZqPiClZwelistjEdLemTbKcjET4Cd4hHetNMixtF2Yyl5x1zQG+sF33BtOSEq5h/+/d9Ry9pGeualP6M3L/93eualP6OWtY30/zz3V4KoWVXsJ3FerbION0vkUfBFQH4DsMV1+R00vAsvZkR8N6WUFaNceRaFELxpzUeesJI1ckMR8A2E3B6cC/kq0nyvF+NiMNxGjMlT3QUD5IM68PUI1pkLslfyz/oiIWVCzPeoLBMZkwqSvkd2TrCeQ8HTVXkVGpQUpvVRV8LwLFp8wct2LGrbuoGeeenP6J2hH4g/z7z0Z7Ruc4svUU0mJN1KkWl70zV4xgNfEPQmLRtCFw6OsZe17WIWxixJMsn13ctWufmYqKHcErmRj4Bvi6nIxcCKp9H5X1/JmoR8NZ8tKSvDij3bUFJWlnP7qfZu9L30Hi4+95rvdW/qsP/1tq9+Fruf+f2sRgkAboPH55G4MgYAWLZpNUrKS7O24VOhW5/Y69vXwGtH2QTk1z7I2ve1fCfFYiR1Eb2xE2is2uhO821DKBRCQ8VajKV7fdOEK8PVGE5dyJo8TACWla1C1BwFQCgNlaOpahM21OxEfUULkvYMRlIXxTThtB0DUQYRfQAhhJG2E7AzpjtReCcaqzZiaWkdNK0EI6lL6Il9hNFUD3QnDiAD3Y6ju6sP23dv8p3H9t2bcOXSCOorWgFoqC1bBUDDyoo7AGgY13uhaRpWVKx1G0rWABoQtyZBcJCyY1he3oSYOQEnY2HDsp1wyPJNVU5YEfe/u+BkzLwTjPmUZiCDuvKWnN8bb9ooDZUDCKFlyVY0V22+pp+nPJVZYXbc9p1wHHMZFjnbZ8NLyrHqwbsAMBK7+NzP0fbVz6K0uhJWPI3J41345M//7yyCzteVF+wwC6KkLIy6uzcUda7BfbU+sQepoQhan7h/1uu6Hmiq2ozq0gZo8HddRc1RNFZtdLdhv8xy91V1aT2WltYB0JC2Y0jZM1he3iSGcQIhVJc2AAihMlyDivASsA4vNhAV0FBf0YqR1EVUhpcC0BDRB9BctcXtjluF8pIlUmfYRrRHDmBF5TrUljVi05aN6Dh2CTse3CrOuePYJaxvWwuAoEHDjDmKuooWTOoDyMAW5768vAn1FathOilEjAHxegglyMBGc9UWxK1JxPVJTKT7sb3+ccgDSTnBxcxxlITKAZA7sJOda75Ot0IDP1PWDBoq1vg6Da8GwUGg3jDRNjXqPgduCwIOkmAu5CO/YlDos0ESK0RqsxHt9cDF517LaoPmuJbvpHiQ2xZc73u1pmwlIvogmqu2oCTEWqvlFuOOyFtYUbkO1aX16I2dwD31n8qaLFxbvgp2xoad0VEWqkJjxQZkMhmUhEqRsqOYMUfQE/sI1aUNgrA21KRFe3NL1VYkrRnRLszbfjVo+A///j/iz/706/iT//IVbN+9CR3HLuGpr/8Av/Vnv4aR1CVUl9ZjeXkTpvRh1JStQGW4BrVlTagKL0PSmgJKQiBxTewmE9EHUF+xHpN6P4aSFwTxaihBbVkjWK0fQnPVZkzq/agrb0aGbIyle8R115e3oDd2QiJtdsPZULMzb1Ua0QdQV8Gq5FWV6xHRB7Gq6o55+emqluVZkEuXyPfnZtWAr8VCda0a6bUEvd8IXM/zKWZBJmi9ymdLkzu15KAeWePM1UkWDJ7hn/c7DQzfucpZvdzm5sU/9oggnv/nub+idZtbKBQK0ZZtbfT8P/xAHJ9HS7KW6FRgkc8Qi2lRfVyMNPKsc/7W4kh6UBybL5ZxndWw0llde7y7j19r0FESRPZYqPmzpKkGDgbczotw10Iyc01LU/Aw24KMJa3258uAkNPO8mUVeATjRjvauiCSYLMFEflmsFmOQYaVElMsGCHKI4LO+rzDhp2imBHJSmGzHZtMSw9kEPsbJILXKOcLy9eafcMxpZuMHDZvCP+yf4HR39EX9BTn/ll47dkK8498BHxbSBDX8mg/17Q0BQ9yslYuEByMpLrRVNWGynA1+CPzpN4vUsOWhGvzPsbaGRsAgZDBjDmCyvBS2BkD43ofJtL9aK7ajKWl9VhSWus7j6rwMimZTBMLT/y1j9U/gfqKVvexvQ1mRofuxNBStQUz5hiTFFCNmDmOlqotIJDQTtNOAg6ZWFGxDkOp876UNk+Hds+jtFZ67B9AaagcEX0Aq6rWo7q0AQQHM8YYDCfp6tsX0FTVhpg57jvniXQ/1tfch7F0DzLkoLq0IUta4eeQD0zmaALUuvwNxW1BwNeCfOR9Y/TRG4didPK5IrggE8RoqttHrNWl9eiJfoT1y+6TFpom8hJ5wooAgG/BqblqM5qqNmNlxTpkyIGZMZCyplFb1igWgUpCJVmRlbodQ1NVG8pClagqrXVJbguS1hSWlNahNFSKodQFdg5EiBiDaKhYiwwyrnbbipg5gWVlqwBUYcYckRYR2wAQdDuJEEoQ0QexomINhsWNhZGjnTFQEmILs2YmhbQdQ9qJo7Fyo6RvAyGEEdImURqqxKrK9QBYNKXhpFBfuRoAYUPNLiwVC5XsHAiU8+fgXyi7PpSgFuNyQxHwVWIhFsyuJ25URe/9Im7OItalpXWIl0Z8joi6imYAyCJyO2OLfFu5wmUkQygJlWIkdQmNVRtRXsIquyl9CMvKGlnurj6A5qo2dEePoaq0VixsrahYhwn9sq/i1KBh2LWjARoaKloxlLyA8pIlMJwk6spbkLCmUFO2EiWhEiTNadSWNcHMpASxzpijWF7ehAxs1Fesx4w5Ki3AMXIc1/vQVNUGO2MjZk6gvqIVydRMYLGOkXlEH0R1aQOS1pS4UTRUrAGBfDc+J+OgoWINeqLHUVVam/OGWGihbL6IUy3G5YYiYAUAN66iD/4iyr+MhSrmIBFE9CuwMxZqy5uwpLQGtWWNGEv3oKZ0JcKhUkzqV0TFWF3agLJQBSN4a1JyPOzCqqoNWFq6HJN6P87PHAJqtUB4uobaskbfzSKiD+Du+k8AxPadgY24NeneCMIoD1cjAxu6k0Q4VI6YNY76itVI2wk0V22BbscAACmLOS2cjIWkM4OJdD8AoKVqC0JaCAlrChPpfpSFKlFfsca11WlIWTOor2gVskfUHEX71AFsqNmZJTNM6v1YXt6EqtJleaWg4I1Q/q4j+sC8EOdsctTtCkXAtwiuVUK4URX9XH8R7YyFhDXlkxlal24THt7yEnatleEaWBkdleFqRPQBn8SgoQQagOFUF1JWFBuW7XLPZROsjCnJHjtRX9EKK5N2z8+zvLUs2YKWqi2Y0C+LKRX15atRXrLEJ6U0V7bBIQOhUBiGk0R1aT1qSllDBtOpq1EersZUahhNVZsRCoWQQQhxfRLb6x+HBg0ZZLC8vAUjqYvYXv84QggLrXfTsj2oKl2OkVSXsIw1VKzBhpqdWFXJLGwNFWuFda++ojXLzhdE8MYn3ySbqzZjQ41+zcQ5mxx1u0IR8C2Ca5EQrof+mw/8F9HO2BhIdIoRPxH9Ss4GAD6qKNiMkKspo66iWYzh2Vr7MFZVrsd4ug9hrQxLw8vRVLUJCWsaEX0AVkZ3yasVVaXLoLkNEkAGE3o/mqo2oblqMwiEFZVrUV/RCgKhrqLF7ZbbgEzGRtqJinNqqtoIAmA6BlLmGOrKWxC3IlhaWo+IqMjZ+U6k2TGcjC1dC1BRshS6S9x8TNCqqjtcyYaNSaoILxGV8YqKdQiFQmiu2iKq3Un9ivDxhkOlc/b0FjuWSOHaoQj4FsG1SAgL4egYkRaVqksbYJOJhDWF2vJVvu04GQQ75XI1ZbQu3SZer69YDUBDhhzUV65B2o4BCLnNGRbMlI76itUgsJltGkoQ1spE6zHc16vCNWip2opQiLkDKENu556GklA5HMdm+3X3Man3w85YjKDhCGmioWKtW0luBBDC+pr7kLCmYThJsZDmVZnsWFtrH0Z9xWqMpXpdWcTToTct24PKcDWGUueFLNNQsRaT+hX32v2wMzYIDkZd10khPTdftaoW0uYfioBvEVwPq931hH9RScPS0jokrCnYGdu3Ep+PDORKekXlOkFewe1bl94JO2OJx387YyNtx9FctVk8kleGq8Wjuyw9aCjBePoyGipbMZEaQkPFWmjQUF3aAN1JorykCmZGR1nJElSWLEXSmhLSCKD5pImWqi2oL28BEELMHENtWRMyyGBJaS2m9GE0V20WC4L8/FdV3YGBRCcb4GmW+7rmKJPJ0tNLQiV5q10rk5Z0cSYt8EXGYslULaTNP5TpT8EX1jMf4EEwcvhL8DVZBgiHwiB3UjHBmdP+w6FwzkAavo2TcXxhNhqAGXMEGdhi24g+IFwPAFBf3oIQwoiZ46gtX4UpfUi8T8iAyEF5qALkVrgEBxaZWFJaJ441qV8R4T5NVZtgZNIoDVUgZo6jrqIFoVAIEf0KxtN9qC6tB4H5gpuqNrr+Zla1NlW1YUl4OZaVNUrf2QBKQqUi+KaxaoP4TL7vi9v5uL2Pe61HUpeK/bG6gUlMflGYHygCVph3eIR3Mcdr7Be+vqIVpaFK8bjMq8XRVE/R+4/ogz4ytjM2Zowxn67qESEnniu+43Cblpy8Vl6yBFFzFLVljagMVweS2S4i7SSgaSW+cy4PVYHgiFS3+orViJnjgjDLQuXQNM31CUN8BxnKoKykEprrtiAiRPQBAGC6cfQ4lpc1oyRU4n5nFaivaEUoFEI4VIrq0np0RN4Sn8n3fZ2fOYSIPoCWqi0Ih0p9Wnax0FAigpMU5gdKglCYd/jlBfk1La9UIL8/luplUY1Sypdc4fJtGyrWBDra2txgn+U+LZgfi1eyvMONa5qNVRsDjRlATdkqn74qvx9CCZyM5Vt8y1AGI+lLoitNQwg1ZSuRtGdQV96MqDmGynANykJV4jrCoVJGuiCMuB1xU8YQGirWIGnFBOGGQiUYSHSiqWoTQgj7wnKWltajZclW1FesdrfJlhT4z2F5eRMm9H6sqrrjqsg0HAqLgKN8x1KYG1QFfA24EXm5NyMY4d3p++XkJJjvF5a/H9EHcH7mEBJWJKtqDm5bEioRj8WshfmKu303NISyjldTthLTxgiaq7YgHAqL/Y+muhFCCUtWi55Awoogbcd8x5azcwkQi3K8fTdisEp7ReU6LC2tQ8aVBKpLG6BpYdSUrcSkfgWEDJyMg7FUL+yMjarwMoy6i2tj6V7RTJGyp9iiZFmj9D10Y0lpLeorWqW8X8Kqqjvyflf83JurtmDaGBVPHOFQGNWlDcJPHUQuGYmDL6DORb5QyA1VAV8DVB7E/INlMMhttIU9w7ySA0Lis9w+FUREH0DSnkapWYG6imapgt2EUCjEciOW1QqnwK4Vv4aKkiVZ++F5uxPpfmxd/pAgpK21D6GlagsyyCAUCovq/N76z2Tl8y4vb3JzH+7wVf+6k0J5SRWWlzdjJHXJreY3i/f5DYXb7fiCGM9VDsZ6cuRaoOPnt6FmV9aiWqEFN9VUMX9QBHwNuNXyIBYDZGnCztioLq0HC1DPt33YZ10rtDpfX7EG0DXUlK3AlD6EmrJVgrydjAM7o2NCBAExSSPoFMhkMr4w+NJQpXjEr69oxYw5guoy9mjPX/cCgSAFu69Fc9Vm1/XhXXM4VIpMJoOhQLZx8LrksPqkFUN5SZUrv9TBztgYSXW5xJ1bxmGfzU+khd5TTRXzByVBXAPm2z2g4MdIqgunI78ouMBUDIKP6xF9ADVlK8X+R1JdAAhhrQxslNEuIWlMpPuRsKaEbJCBg+FUFwC4Ieme5BIzx9E+dQBxcxIaQr5FON1OsgQz8oLdu6PHfAuVHKFQyOegYHKFXwrQUOKOOiJMGQMgOJhI9/vGFvllnItwMn6HSSFZaDbJSGF+oCpghUULlk5WVXCBqRgEH6cb3JlsvAGi0SXb8pIlqCldIVLZNizbibqKFoymurG0dDlsMv1da6GlCIdKYTiE8pIq1JStxNbah1FTtlIs4FkZQywE2hkbEWNI5DXUuqOJZPDWa8NJYkm4VmjiXCaQmyFKQxVS5KWG9TX3ico8mIbG2pSvzNukC4X5gSJghUUL3kYb1DvnCu9xmkkC3NLFMxKi5hjqKlqgQYOdMd1UtkloKMGI5LKoL1+NspJKaV/e433KmkZN+YrA+cLNC+bXE8aqqjsKdpRF9AExjmhKH/bp2oD/ZlJb1ojGyg3iGuUGFvl7Ym3K2R1yqrNt4aEIWGHR41oXfbyuOctXSZeXVGEw0YnVS7chZcdQGV6KqDWGDDmwMjqi5lgg1Cfk0z/9RLsVVsbAlD4kne9GZMhBxBjyVZ5yQ8WqKlaFy2QIsOZr/pl8dj15kCgh47u2ILnmqnyvtrMtH3ErQp87FAErLHrMZdEnSAK5oxVZizKLp4yAAFSXscWr5eXNIGRgpnTUlK3wNTvwvAkO2e9sZNKImWPCZdG6dBsymQxmrFF3TL2H+opWmKm073WZDBsqWpFveSb4XXBiHUhc8JFpMeR6tTe2fPtWrcpzhyJghVsKQRKQNdvmqi3YUJMWxBkks3AojIFEp2imSNtxVJfVYWlpnS9vgiNmjmNJuFZMwuDEWlO2MquitTMmRlKX8mbsymR4NdVjkEzlyj2Yr+Fd79W5GeRjyY4LZU+bOxQBK9xSyE1E7G8WrXhnUZ9fUlorusTyERVzUlwSvmNehcqz2MpCVWioaPUlmeXK2L1Wa1f2zSR/5X6tyC3D5LbLKRSGImCFmx5B2SF7ykZh0pUxFyJkHWab3ckUa6RkN88n3FCxxue4uJEZu/kq92JRjKarqt5rg/IBK9z0KNSGe73AF/QysDGUvICR1EXJOxsG73gjEOorWjFtjLot0PO3OFWoXRi4di9vMd+rfIzZzkchG6oCVripkKsqC9rMrmVfxW4na81blz+E0pC/GYe3J3P/7vXw317vRa+5VrdqEW7uUBWwwqJGsKrKVZV5sgHNqQIrtnLOtZ0ccRkzJ4DAyHf5/bleJ08bm+06ijnGtVSlc62g53rNCqoCVljkCFZVhaqyuVZgxVZ4ubaTIy55p1pwysRcqsDgjLtirqOYY9zIqlRlRMwdioAVFjVmyxEutO1sKJYwcm0nyxJ8dtukFOQTbBuerYoMNljIlaS3n8LhOrPvV2GxQRGwwqLGXF0JV9uwMft2m31e2lyVZaG24dnOK3uWXXaDg2xvK7aiVVXp4oYiYIXbEsWS40jqIibS/Wis2oiBRJcg7EKyBMe1VJ/yDYLnAc+WkaxagW8+qEU4hUWD62VjyrXfQgtG8vZNVZuxvuY+Mf8tOCED0Hz79g8MLW4RK9f5yQt/3uDRcMF9LoQdT+HaoCpghUWD67VglLCmMJHu9+230KN58Dxqy1flrTwj+hUx3VkeDTSXa8j1maupnpXee/NBEbDCosH1IBA7YyFuTWJ7/eM5B1AW9hXP3irsBeuszvvZ2aSBuRyvEJTee/NBSRAKiwbBx+v5kCS8wZs9OQNpCvuKtVmPH/x8LolgNmkg12dUV9ntAVUBKyxaXHte7ewJXYV9xV2zHr+Yqv1qKnvVVXZ7QBGwwqLFfOXVeoE5rVkSwLX6iot57L8aaUDpubcHFAErLFrMR14tUHj8+vU4/nxA6bm3BxQBK9xymE8/roLC9YRahFO45XGjR6zP9wKaWpC7daEIWOGWx40msPluiFANFrculAShcMvjRjsK5lvyUBLKrQtFwAq3PG40gc33AppakLt1oQhY4ZaHIjCFxQqlASsoKCgsEBQBKygoKCwQFAErKCgoLBAUASsoKCgsEBQBKygoKCwQFAErKCgoLBAUASsoKCgsEDQiKn5jTZsA0H/9TkdBQUHhlsRaIloRfHFOBKygoKCgMH9QEoSCgoLCAkERsIKCgsICQRGwgoKCwgJBEbCCgoLCAkERsIKCgsICQRGwgoKCwgJBEbCCgoLCAkERsIKCgsICQRGwgoKCwgLh/w++OZbHecGaSQAAAABJRU5ErkJggg==\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",
"\n",
"Try to cluster the above dataset into 3 clusters. \n",
"Notice: do not generate data again, use the same dataset as above.\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# write your code here\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()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<details><summary>Click here for the solution</summary>\n",
"\n",
"```python\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",
"\n",
"</details>\n"
]
},
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"cell_type": "markdown",
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"source": [
"<h1 id=\"customer_segmentation_K_means\">Customer Segmentation with K-Means</h1>\n",
"\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)\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
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},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2021-03-20 13:59:00-- https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-ML0101EN-SkillsNetwork/labs/Module%204/data/Cust_Segmentation.csv\n",
"Resolving cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud (cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud)... 169.63.118.104\n",
"Connecting to cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud (cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud)|169.63.118.104|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 33426 (33K) [text/csv]\n",
"Saving to: ‘Cust_Segmentation.csv’\n",
"\n",
"Cust_Segmentation.c 100%[===================>] 32.64K --.-KB/s in 0.002s \n",
"\n",
"2021-03-20 13:59:01 (14.2 MB/s) - ‘Cust_Segmentation.csv’ saved [33426/33426]\n",
"\n"
]
}
],
"source": [
"!wget -O Cust_Segmentation.csv https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-ML0101EN-SkillsNetwork/labs/Module%204/data/Cust_Segmentation.csv"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"### Load Data From CSV File\n",
"\n",
"Before you can work with the data, you must use the URL to get the Cust_Segmentation.csv.\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
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},
"outputs": [
{
"data": {
"text/html": [
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <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",
" <th>Other Debt</th>\n",
" <th>Defaulted</th>\n",
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" <td>7.2</td>\n",
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" </tbody>\n",
"</table>\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": 12,
"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\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
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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.\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
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},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <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",
" <th>Other Debt</th>\n",
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" <td>0.0</td>\n",
" <td>7.2</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 \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": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = cust_df.drop('Address', axis=1)\n",
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"#### Normalizing over the standard deviation\n",
"\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.\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
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},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 0.74291541, 0.31212243, -0.37878978, ..., -0.59048916,\n",
" -0.52379654, -0.57652509],\n",
" [ 1.48949049, -0.76634938, 2.5737211 , ..., 1.51296181,\n",
" -0.52379654, 0.39138677],\n",
" [-0.25251804, 0.31212243, 0.2117124 , ..., 0.80170393,\n",
" 1.90913822, 1.59755385],\n",
" ...,\n",
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]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"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>\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
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},
"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.\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
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},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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" 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 0]\n"
]
}
],
"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,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"<h2 id=\"insights\">Insights</h2>\n",
"\n",
"We assign the labels to each row in dataframe.\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
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" <th>Edu</th>\n",
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" <th>Income</th>\n",
" <th>Card Debt</th>\n",
" <th>Other Debt</th>\n",
" <th>Defaulted</th>\n",
" <th>DebtIncomeRatio</th>\n",
" <th>Clus_km</th>\n",
" </tr>\n",
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" <td>5.802</td>\n",
" <td>1.0</td>\n",
" <td>20.9</td>\n",
" <td>1</td>\n",
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" <th>3</th>\n",
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" <th>4</th>\n",
" <td>5</td>\n",
" <td>47</td>\n",
" <td>1</td>\n",
" <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>2</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 1 \n",
"1 0.0 12.8 0 \n",
"2 1.0 20.9 1 \n",
"3 0.0 6.3 1 \n",
"4 0.0 7.2 2 "
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[\"Clus_km\"] = labels\n",
"df.head(5)"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"source": [
"We can easily check the centroid values by averaging the features in each cluster.\n"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <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",
" <th>Other Debt</th>\n",
" <th>Defaulted</th>\n",
" <th>DebtIncomeRatio</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Clus_km</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <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>403.780220</td>\n",
" <td>41.368132</td>\n",
" <td>1.961538</td>\n",
" <td>15.252747</td>\n",
" <td>84.076923</td>\n",
" <td>3.114412</td>\n",
" <td>5.770352</td>\n",
" <td>0.172414</td>\n",
" <td>10.725824</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>432.006154</td>\n",
" <td>32.967692</td>\n",
" <td>1.613846</td>\n",
" <td>6.389231</td>\n",
" <td>31.204615</td>\n",
" <td>1.032711</td>\n",
" <td>2.108345</td>\n",
" <td>0.284658</td>\n",
" <td>10.095385</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</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",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Customer Id Age Edu Years Employed Income \\\n",
"Clus_km \n",
"0 403.780220 41.368132 1.961538 15.252747 84.076923 \n",
"1 432.006154 32.967692 1.613846 6.389231 31.204615 \n",
"2 410.166667 45.388889 2.666667 19.555556 227.166667 \n",
"\n",
" Card Debt Other Debt Defaulted DebtIncomeRatio \n",
"Clus_km \n",
"0 3.114412 5.770352 0.172414 10.725824 \n",
"1 1.032711 2.108345 0.284658 10.095385 \n",
"2 5.678444 10.907167 0.285714 7.322222 "
]
},
"execution_count": 17,
"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:\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"button": false,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
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\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": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x7f871585e048>"
]
},
"execution_count": 19,
"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,
"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\n"
]
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"<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=\"https://www.ibm.com/analytics/spss-statistics-software\">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://www.ibm.com/cloud/watson-studio\">Watson Studio</a>\n"
]
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"### Thank you for completing this lab!\n",
"\n",
"## Author\n",
"\n",
"Saeed Aghabozorgi\n",
"\n",
"### Other Contributors\n",
"\n",
"<a href=\"https://www.linkedin.com/in/joseph-s-50398b136/\" target=\"_blank\">Joseph Santarcangelo</a>\n",
"\n",
"## Change Log\n",
"\n",
"| Date (YYYY-MM-DD) | Version | Changed By | Change Description |\n",
"| ----------------- | ------- | ---------- | ---------------------------------- |\n",
"| 2020-11-03 | 2.1 | Lakshmi | Updated URL of csv |\n",
"| 2020-08-27 | 2.0 | Lavanya | Moved lab to course repo in GitLab |\n",
"| | | | |\n",
"| | | | |\n",
"\n",
"## <h3 align=\"center\"> © IBM Corporation 2020. All rights reserved. <h3/>\n"
]
}
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