:py:mod:`ForeTiS.model._tensorflow_model` ========================================= .. py:module:: ForeTiS.model._tensorflow_model Module Contents --------------- Classes ~~~~~~~ .. autoapisummary:: ForeTiS.model._tensorflow_model.TensorflowModel .. py:class:: TensorflowModel(optuna_trial, datasets, featureset_name, optimize_featureset, pca_transform = None, target_column = None) Bases: :py:obj:`ForeTiS.model._base_model.BaseModel`, :py:obj:`abc.ABC` Parent class based on :obj:`~ForeTiS.model._base_model.BaseModel` for all TensorFlow models to share functionalities. See :obj:`~ForeTiS.model._base_model.BaseModel` for more information. **Attributes** *Inherited attributes* See :obj:`~ForeTiS.model._base_model.BaseModel`. *Additional attributes* - x_scaler (*sklearn.preprocessing.StandardScaler*): Standard scaler for the x data - y_scaler (*sklearn.preprocessing.StandardScaler*): Standard scaler for the y data .. py:method:: define_model() Definition of the actual prediction model. See :obj:`~ForeTiS.model._base_model.BaseModel` for more information. .. py:method:: retrain(retrain) Implementation of the retraining for models with sklearn-like API. See :obj:`~ForeTiS.model._base_model.BaseModel` for more information .. py:method:: update(update, period) Implementation of the retraining for models with sklearn-like API. See :obj:`~ForeTiS.model._base_model.BaseModel` for more information .. py:method:: predict(X_in) Implementation of a prediction based on input features for models with sklearn-like API. See :obj:`~ForeTiS.model._base_model.BaseModel` for more information .. py:method:: train_val_loop(train, val) Implementation of a train and validation loop for models with sklearn-like API. See :obj:`~ForeTiS.model._base_model.BaseModel` for more information .. py:method:: extend_kernel_combinations() Function extending kernels list with combinations based on base_kernels .. py:method:: common_hyperparams() :staticmethod: See :obj:`~ForeTiS.model._base_model.BaseModel` for more information on the format.