neurosynth/analysis/classify.py
def fit_dataset(self, dataset, y, features=None,
                    feature_type='features'):
        """ Given a dataset, fits either features or voxels to y """

        # Get data from dataset

        if feature_type == 'features':
            X = np.rot90(dataset.feature_table.data.toarray())
        elif feature_type == 'voxels':
            X = np.rot90(dataset.image_table.data.toarray())

        self.sk_classifier.fit(X, y)
def fit_dataset(self, dataset, y, features=None,
                    feature_type='features'):
        # Get data from dataset

        if feature_type == 'features':
            X = np.rot90(dataset.feature_table.data.toarray())
        elif feature_type == 'voxels':
            X = np.rot90(dataset.image_table.data.toarray())

        self.sk_classifier.fit(X, y)
def fit_dataset ( self , dataset , y , features = None , feature_type = 'features' ) : # Get data from dataset if feature_type == 'features' : X = np . rot90 ( dataset . feature_table . data . toarray ( ) ) elif feature_type == 'voxels' : X = np . rot90 ( dataset . image_table . data . toarray ( ) ) self . sk_classifier . fit ( X , y )
Given a dataset, fits either features or voxels to y
Given a dataset fits either features or voxels to y