preprocessing.py 文件源码

def __init__(self, n_values, feature_indices):
        import warnings
        from sklearn.preprocessing import OneHotEncoder

        if not isinstance(n_values, np.ndarray):
            n_values = np.array(n_values)
        if not isinstance(feature_indices, np.ndarray):
            feature_indices = np.array(feature_indices)
        assert feature_indices.size > 0
        assert feature_indices.shape == n_values.shape
        for nv in n_values:
            if nv <= 2:
                raise Exception("Categorical features must have 3+ labels")

        self.feature_indices = feature_indices
        self.n_values = n_values
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            self.encoder = OneHotEncoder(n_values=n_values, sparse=False)
        self.columnlabels = None
        self.xform_start_indices = None