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All Samples(6)  |  Call(6)  |  Derive(0)  |  Import(0)

src/p/y/py-sdm-HEAD/sdm/sdm.py   py-sdm(Download)
            label_names = train_labels
            label_encoder = LabelEncoder()
            train_labels = label_encoder.fit_transform(label_names)
            label_class_names = label_encoder.classes_
 
            label_names = labels
            label_encoder = LabelEncoder()
            labels = label_encoder.fit_transform(label_names)
            label_class_names = label_encoder.classes_
 

src/c/o/copper-0.0.4/copper/transform.py   copper(Download)
    else:
        le = LabelEncoder()
        encoded = le.fit_transform(dataset[cols[0]].values)
        return le, encoded
 

src/c/o/copper-HEAD/copper/transform.py   copper(Download)
    else:
        le = LabelEncoder()
        encoded = le.fit_transform(dataset[cols[0]].values)
        return le, encoded
 

src/p/e/pegasos-HEAD/pegasos/base.py   pegasos(Download)
 
        self._enc = LabelEncoder()
        y = self._enc.fit_transform(y)
 
        if len(self.classes_) != 2:

src/p/y/py-sdm-HEAD/sdm/tests/test_sdm.py   py-sdm(Download)
        feats = Features.load_from_hdf5(os.path.join(data_dir, name + '.h5'))
        le = LabelEncoder()
        y = le.fit_transform(feats.categories)
 
        for div_func in div_funcs: