spkit.PCA

class spkit.PCA(n_components=None, apply_whitening=True, tol=1e-05)

Principle Component Analysis

TO BE IMPROVED - Not TESTES

Parameters:

X: (n,c)

Returns:

W - c X c

Methods

fit(X)	Fitting by computing SVD of Covariance Matrix
fit_transform(X)	Fit model and apply transformation
transform(X)	Transform given matrix X
whitening(X)	Whitening of matrix

fit(X)

Fitting by computing SVD of Covariance Matrix

Parameters:

X: 2D array (n,c)

• n - number of samples

• c - number of channels (dimensions)

Returns:

Wc by c Matrix

• Transformation Matrix

• X.dot(W)

fit_transform(X)

Fit model and apply transformation

Parameters:

X: 2D array (n,c)

• n - number of samples

• c - number of channels (dimensions)

Returns:

Xpca: Transformed Matrix

transform(X)

Transform given matrix X

Parameters:

X: 2D array (n,c)

• n - number of samples

• c - number of channels (dimensions)

Returns:

Xpca: Transformed Matrix

whitening(X)

Whitening of matrix