[pycon] Task 2
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- D = np.genfromtxt("./iris.csv", delimiter=",",skip_header=1)
- def pdf_multivariate_gauss(x, mu, cov):
- part1 = 1 / ( ((2* np.pi)**(len(mu)/2)) * (np.linalg.det(cov)**(1/2)) )
- part2 = (-1/2) * ((x-mu).T.dot(np.linalg.inv(cov))).dot((x-mu))
- return float(part1 * np.exp(part2))
- # add code and markdown cells as needed
- D0 = D[D[:,4] == 0]
- D0 = D0[:, 0:4]
- D1 = D[D[:,4] == 1]
- D1 = D1[:, 0:4]
- D2 = D[D[:,4] == 2]
- D2 = D2[:, 0:4]
- mu0 = D0.mean(axis=0)
- mu1 = D1.mean(axis=0)
- mu2 = D2.mean(axis=0)
- cov0 = np.cov(D0.T)
- cov1 = np.cov(D1.T)
- cov2 = np.cov(D2.T)
- p0 = len(D[D[:,4] == 0])/(len(D)-1)
- p1 = len(D[D[:,4] == 1])/(len(D)-1)
- p2 = len(D[D[:,4] == 2])/(len(D)-1)
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