abhishek-Kumar009

count_outliers = len(listOfOutliers)
print('\n\nNumber of outliers:', count_outliers)
print('\n',listOfOutliers)

abhishek-Kumar009

plt.scatter(X[:, 0], X[:, 1], marker = "x")
plt.xlabel('Latency(ms)')
plt.ylabel('Throughput(mb/s)')
plt.scatter(X[listOfOutliers,0], X[listOfOutliers, 1], facecolors = 'none', edgecolors = 'r')
plt.show()

abhishek-Kumar009

newDataset = sio.loadmat('anomalyDataTest.mat')

Xtest = newDataset['X']
Xvaltest = newDataset['Xval']
yvaltest = newDataset['yval']

abhishek-Kumar009

mutest, sigma2test = estimateGaussian(Xtest)

ptest = multivariateGaussian(Xtest, mutest, sigma2test)

pvaltest = multivariateGaussian(Xvaltest, mutest, sigma2test)


F1test, epsilontest = selectThreshHold(yvaltest, pvaltest)
print('\nBest epsilon and F1 are\n',epsilontest, F1test)

abhishek-Kumar009

outliersTest = ptest < epsilontest
listOfOl = findIndices(outliersTest)

print('\n\n Outliers are:\n',listOfOl)
print('\n\nNumber of outliers are: ',len(listOfOl))

abhishek-Kumar009

mutest, sigma2test = estimateGaussian(Xtest)
ptest = multivariateGaussian(Xtest, mutest, sigma2test)
pvaltest = multivariateGaussian(Xvaltest, mutest, sigma2test)

F1test, epsilontest = selectThreshHold(yvaltest, pvaltest)
print('\nBest epsilon and F1 are\n',epsilontest, F1test)