def set_params(self, *, params: Params) -> None: self._label_encoder = params['label_encoder'] self._output_columns = params['output_columns'] self._ts_sz = params['ts_sz'] self._n_classes = params['n_classes'] self._is_fit = all(param is not None for param in params.values())
def set_params(self, *, params: TabularSplitPrimitiveParams) -> None: self._dataset = params['dataset'] self._main_resource_id = params['main_resource_id'] self._splits = params['splits'] self._graph = params['graph'] self._fitted = all(param is not None for param in params.values())
def set_params(self, *, params: Params) -> None: self._add_semantic_types = params['add_semantic_types'] self._remove_semantic_types = params['remove_semantic_types'] self._is_fit = all(param is not None for param in params.values())
def set_params(self, *, params: Params) -> None: self._scaler = params['scaler'] self._knn = params['classifier'] self._output_columns = params['output_columns'] self._is_fit = all(param is not None for param in params.values())
def set_params(self, *, params: Params) -> None: self._label_encoder = params["label_encoder"] self._output_columns = params["output_columns"] self._ts_sz = params["ts_sz"] self._n_classes = params["n_classes"] self._is_fit = all(param is not None for param in params.values())
def set_params(self, *, params: Params) -> None: self.encoder = params['label_encoder'] self.output_columns = params['output_columns'] self._is_fit = all(param is not None for param in params.values())