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Created on Skills Network 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>"
]
},
{
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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,
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"outputs": [],
"source": [
"np.random.seed(0)"
]
},
{
"cell_type": "markdown",
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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"
]
},
{
"cell_type": "code",
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"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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"source": [
"Display the scatter plot of the randomly generated data."
]
},
{
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"execution_count": 3,
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"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7f2b02d16358>"
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"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
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{
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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": 4,
"metadata": {
"button": false,
"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": 5,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"jupyter": {
"outputs_hidden": false
},
"new_sheet": false,
"run_control": {
"read_only": 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": 5,
"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": 6,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"jupyter": {
"outputs_hidden": false
},
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([1, 3, 0, ..., 0, 3, 0], dtype=int32)"
]
},
"execution_count": 6,
"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": 7,
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"data": {
"text/plain": [
"array([[-2.02188472, -0.98953116],\n",
" [ 3.9822482 , 4.01718986],\n",
" [ 2.03068042, -3.08061692],\n",
" [ 1.02784026, 0.98322674]])"
]
},
"execution_count": 7,
"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": 9,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"jupyter": {
"outputs_hidden": false
},
"new_sheet": false,
"run_control": {
"read_only": 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": 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",
"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": [
"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": 11,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"jupyter": {
"outputs_hidden": false
},
"new_sheet": false,
"run_control": {
"read_only": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2020-06-18 05:25:26-- 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)... 67.228.254.196\n",
"Connecting to s3-api.us-geo.objectstorage.softlayer.net (s3-api.us-geo.objectstorage.softlayer.net)|67.228.254.196|: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",
"2020-06-18 05:25:26 (1.49 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"
]
},
{
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"metadata": {
"button": false,
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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": 12,
"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": 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"
]
},
{
"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": 13,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
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},
"outputs": [
{
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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",
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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": 13,
"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": 14,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"jupyter": {
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"run_control": {
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},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 0.74291541, 0.31212243, -0.37878978, ..., -0.59048916,\n",
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" ...,\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>"
]
},
{
"cell_type": "markdown",
"metadata": {
"button": false,
"deletable": true,
"new_sheet": false,
"run_control": {
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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."
]
},
{
"cell_type": "code",
"execution_count": 15,
"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
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},
"source": [
"<h2 id=\"insights\">Insights</h2>\n",
"We assign the labels to each row in dataframe."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"button": false,
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},
"outputs": [
{
"data": {
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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>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": 16,
"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": 19,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"jupyter": {
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"run_control": {
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}
},
"outputs": [
{
"data": {
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" <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": 19,
"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": 20,
"metadata": {
"button": false,
"collapsed": false,
"deletable": true,
"jupyter": {
"outputs_hidden": 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": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x7f2af00ea278>"
]
},
"execution_count": 23,
"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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