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amankharwal/principal component analysis.py Secret

Created February 20, 2021 09:39
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principal component analysis.py
X_centered = X - X.mean(axis=0)
U, s, Vt = np.linalg.svd(X_centered)
c1 = Vt.T[:, 0]
c2 = Vt.T[:, 1]
m, n = X.shape
S = np.zeros(X_centered.shape)
S[:n, :n] = np.diag(s)
np.allclose(X_centered, U.dot(S).dot(Vt))
W2 = Vt.T[:, :2]
X2D = X_centered.dot(W2)
print(X2D)
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