1
+ {
2
+ "nbformat" : 4 ,
3
+ "nbformat_minor" : 0 ,
4
+ "metadata" : {
5
+ "colab" : {
6
+ "name" : " 36.Agglomerative_Clustering.ipynb" ,
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+ "provenance" : []
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+ },
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+ "kernelspec" : {
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+ "name" : " python3" ,
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+ "display_name" : " Python 3"
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+ }
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+ },
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+ "cells" : [
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+ {
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+ "cell_type" : " code" ,
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+ "metadata" : {
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+ "id" : " yUXGcC4KLmcL"
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+ },
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+ "source" : [
21
+ " import numpy as np\n " ,
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+ " import matplotlib.pyplot as plt\n " ,
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+ " import pandas as pd"
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+ ],
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+ "execution_count" : 1 ,
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+ "outputs" : []
27
+ },
28
+ {
29
+ "cell_type" : " code" ,
30
+ "metadata" : {
31
+ "id" : " 9RlmPzZGLtGi"
32
+ },
33
+ "source" : [
34
+ " dataset = pd.read_csv('Data.csv')\n " ,
35
+ " X = dataset.iloc[:, [2, 3]].values"
36
+ ],
37
+ "execution_count" : 2 ,
38
+ "outputs" : []
39
+ },
40
+ {
41
+ "cell_type" : " code" ,
42
+ "metadata" : {
43
+ "id" : " zWs6ciOoL1b3"
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+ },
45
+ "source" : [
46
+ " import scipy.cluster.hierarchy as sch"
47
+ ],
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+ "execution_count" : 3 ,
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+ "outputs" : []
50
+ },
51
+ {
52
+ "cell_type" : " code" ,
53
+ "metadata" : {
54
+ "id" : " cjEfU6ZSMAPl"
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+ },
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+ "source" : [
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+ " from sklearn.cluster import AgglomerativeClustering\n " ,
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+ " hc = AgglomerativeClustering(n_clusters = 2, affinity = 'euclidean', linkage = 'ward')\n " ,
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+ " y_hc = hc.fit_predict(X)"
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+ ],
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+ "execution_count" : 4 ,
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+ "outputs" : []
63
+ },
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+ {
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+ "cell_type" : " code" ,
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+ "metadata" : {
67
+ "id" : " d0ZYecccMHNx" ,
68
+ "colab" : {
69
+ "base_uri" : " https://localhost:8080/" ,
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+ "height" : 265
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+ },
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+ "outputId" : " 148082ca-3fcc-4d37-bd81-9adb76208333"
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+ },
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+ "source" : [
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+ " plt.scatter(X[y_hc == 0, 0], X[y_hc == 0, 1], s = 100, c = 'red', label = 'Cluster 1')\n " ,
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+ " plt.scatter(X[y_hc == 1, 0], X[y_hc == 1, 1], s = 100, c = 'blue', label = 'Cluster 2')\n " ,
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+ " plt.show()"
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+ ],
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+ "execution_count" : 5 ,
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+ "outputs" : [
81
+ {
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+ "output_type" : " display_data" ,
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+ "data" : {
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+ "image/png": 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\n",
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+ "text/plain" : [
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+ " <Figure size 432x288 with 1 Axes>"
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+ ]
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+ },
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+ "metadata" : {
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+ "tags" : [],
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+ "needs_background" : " light"
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+ }
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+ }
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+ ]
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+ },
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+ {
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+ "cell_type" : " code" ,
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+ "metadata" : {
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+ "id" : " Jxw62UTxwOdw"
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+ },
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+ "source" : [
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+ " "
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+ ],
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+ "execution_count" : 5 ,
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+ "outputs" : []
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+ }
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+ ]
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+ }
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