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())