'Transform dataset.
Parameters
X : array-like or sparse matrix, shape=(n_samples, n_features)
Input data to be transformed. Use ``dtype=np.float32`` for maximum
efficiency. Sparse matrices are also supported, use sparse
``csr_matrix`` for maximum efficiency.
Returns
X_transformed : sparse matrix, shape=(n_samples, n_out)
Transformed dataset.'

def transform(self, X):

    return self.one_hot_encoder_.transform(self.apply(X))
