'Predict regression target for X.
Parameters
X : array-like or sparse matrix, shape = [n_samples, n_features]
The input samples. Internally, it will be converted to
``dtype=np.float32`` and if a sparse matrix is provided
to a sparse ``csr_matrix``.
Returns
y : array of shape = [n_samples]
The predicted values.'

def predict(self, X):

    X = check_array(X, dtype=DTYPE, order='C', accept_sparse='csr')
    return self._decision_function(X).ravel()
