def _daal4py_predict_enet(self, X):
X = make2d(X)
_fptype = getFPType(self.coef_)
elastic_net_palg = daal4py.elastic_net_prediction(fptype=_fptype,
method='defaultDense')
elastic_net_res = elastic_net_palg.compute(X, self.daal_model_)
res = elastic_net_res.prediction
if res.shape[1] == 1 and self.coef_.ndim == 1:
res = np.ravel(res)
return res
def _daal4py_predict_enet(self, X):
X = make2d(X)
_fptype = getFPType(self.coef_)
elastic_net_palg = daal4py.elastic_net_prediction(fptype=_fptype,
method='defaultDense')
if self.n_features_in_ != X.shape[1]:
raise ValueError((f'X has {X.shape[1]} features, '
f'but ElasticNet is expecting '
f'{self.n_features_in_} features as input'))
elastic_net_res = elastic_net_palg.compute(X, self.daal_model_)
res = elastic_net_res.prediction
if res.shape[1] == 1 and self.coef_.ndim == 1:
res = np.ravel(res)
return res