18CSL76 EM algorithm to cluster a set of data stored in a .CSV file.

 Apply EM algorithm to cluster a set of data stored in a . CSV file. Use the same data set for clustering using the k-Means algorithm. Compare the results of these two algorithms and comment on the quality of clustering. You can add Java/Python ML library classes/API in the program.

from sklearn.cluster import KMeans import numpy as np import matplotlib.pyplot as plt import pandas as pd data=pd.read_csv("EM_Algorithm.csv") df1=pd.DataFrame(data) print(df1) f1 = df1['Distance_Feature'].values f2 = df1['Speeding_Feature'].values X=np.matrix(list(zip(f1,f2))) plt.plot() plt.xlim([0, 100]) plt.ylim([0, 50]) plt.title('Dataset') plt.ylabel('speeding_feature') plt.xlabel('Distance_Feature') plt.scatter(f1,f2) plt.show() plt.plot() colors = ['b', 'g', 'r'] markers = ['o', 'v', 's'] kmeans_model = KMeans(n_clusters=3).fit(X) plt.plot() for i, l in enumerate(kmeans_model.labels_): plt.plot(f1[i], f2[i], color=colors[l], marker=markers[l],ls='None') plt.xlim([0, 100]) plt.ylim([0, 50]) plt.show()