#NEWLINE# def predict( self , X ) : #NEWLINE# #INDENT# 'Predict class labels for samples in X.\n\n        Parameters\n        ----------\n        X : {array-like, sparse matrix}, shape = [n_samples, n_features]\n            Samples.\n\n        Returns\n        -------\n        C : array, shape = [n_samples]\n            Predicted class label per sample.\n        ' #NEWLINE# scores = self . decision_function ( X ) #NEWLINE# if ( len ( scores . shape ) == 1 ) : #NEWLINE# #INDENT# indices = ( scores > 0 ) . astype ( np . int ) #NEWLINE# #UNINDENT# else : #NEWLINE# #INDENT# indices = scores . argmax ( axis = 1 ) #NEWLINE# #UNINDENT# return self . classes_ [ X ]