import pandas as pd import numpy as np import matplotlib.pylab as plt import scipy as sp import scipy.stats plt.close("all") dfLoad=pd.read_csv('https://sites.google.com/site/vlsicir/ClassificationSample2.txt', sep='\s+') samples=np.array(dfLoad) x=samples[:,0] y=samples[:,1] N=len(x) numK=2 #Initialize categorial distribution pi=np.ones([1, numK])*(1/numK) mx=np.mean(x) my=np.mean(y) sx=np.std(..

import pandas as pd import numpy as np import matplotlib.pylab as plt plt.close("all") dfLoad=pd.read_csv('https://sites.google.com/site/vlsicir/ClassificationSample.txt', sep='\s+') samples=np.array(dfLoad) x=samples[:,0] y=samples[:,1] N=len(samples) numK=2 f1=plt.figure(1) ax1=f1.add_subplot(111) ax1.plot(x, y, "b.") ax1.set_aspect("equal") mx=np.mean(x) my=np.mean(y) sx=np.std(x) sy=np.std(y..