neurosynth/analysis/classify.py
def set_class_weight(self, class_weight='auto', y=None):
        """ Sets the class_weight of the classifier to match y """

        if class_weight is None:
            cw = None

            try:
                self.clf.set_params(class_weight=cw)
            except ValueError:
                pass

        elif class_weight == 'auto':
            c = np.bincount(y)
            ii = np.nonzero(c)[0]
            c = c / float(c.sum())
            cw = dict(zip(ii[::-1], c[ii]))

            try:
                self.clf.set_params(class_weight=cw)
            except ValueError:
                import warnings
                warnings.warn(
                    "Tried to set class_weight, but failed. The classifier "
                    "probably doesn't support it")
def set_class_weight(self, class_weight='auto', y=None):
        if class_weight is None:
            cw = None

            try:
                self.clf.set_params(class_weight=cw)
            except ValueError:
                pass

        elif class_weight == 'auto':
            c = np.bincount(y)
            ii = np.nonzero(c)[0]
            c = c / float(c.sum())
            cw = dict(zip(ii[::-1], c[ii]))

            try:
                self.clf.set_params(class_weight=cw)
            except ValueError:
                import warnings
                warnings.warn(
                    "Tried to set class_weight, but failed. The classifier "
                    "probably doesn't support it")
def set_class_weight ( self , class_weight = 'auto' , y = None ) : if class_weight is None : cw = None try : self . clf . set_params ( class_weight = cw ) except ValueError : pass elif class_weight == 'auto' : c = np . bincount ( y ) ii = np . nonzero ( c ) [ 0 ] c = c / float ( c . sum ( ) ) cw = dict ( zip ( ii [ : : - 1 ] , c [ ii ] ) ) try : self . clf . set_params ( class_weight = cw ) except ValueError : import warnings warnings . warn ( "Tried to set class_weight, but failed. The classifier " "probably doesn't support it" )
Sets the class_weight of the classifier to match y
Sets the class_weight of the classifier to match y