5.1.1.4.1.3. FedEval.dataset.FedDataBase
5.1.1.4.1.3.1. Module Contents
5.1.1.4.1.3.1.1. Classes
By default, FedData produces datasets for horizontal federated learning |
5.1.1.4.1.3.1.2. Functions
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Divide the data based on the given parameter ratio_list. |
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Input (X, Y) pairs, shuffle and return it. |
- FedEval.dataset.FedDataBase.split_data(data, ratio_list) List[numpy.ndarray]
Divide the data based on the given parameter ratio_list.
- Parameters:
data (ndarray) – Data to be split.
ratio_list (list) – Split ratio, the data will be split according to the ratio.
- Returns:
- The elements in the returned list are the divided data, and the
dimensions of the list are the same as ratio_list.
- Return type:
list
- FedEval.dataset.FedDataBase.shuffle(X, Y)
Input (X, Y) pairs, shuffle and return it.
- class FedEval.dataset.FedDataBase.FedData
By default, FedData produces datasets for horizontal federated learning
- property need_regenerate: bool
- _load_and_process_data()
- abstract load_data()
- iid_data(save_file=True)
- _save_dataset_files(dataset: List[Mapping[str, List[numpy.ndarray]]]) None
- non_iid_data(save_file=True, called_in_iid=False) List[Mapping[str, List[numpy.ndarray]]]