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- calculate_obj(X, Y, W, gamma)
- This function calculates the objective function of rfs
- rfs(X, Y, **kwargs)
- This function implementS efficient and robust feature selection via joint l21-norms minimization
min_W||X^T W - Y||_2,1 + gamma||W||_2,1
Input
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X: {numpy array}, shape (n_samples, n_features)
input data
Y: {numpy array}, shape (n_samples, n_classes)
input class label matrix, each row is a one-hot-coding class label
kwargs: {dictionary}
gamma: {float}
parameter in RFS
verbose: boolean
True if want to display the objective function value, false if not
Output
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W: {numpy array}, shape(n_samples, n_features)
feature weight matrix
Reference
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Nie, Feiping et al. "Efficient and Robust Feature Selection via Joint l2,1-Norms Minimization" NIPS 2010.
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