High-level primitives base classes ================================== High-level primitives base classes provides tools to the developers to easily create new primitives by abstracting some unnecessary and repetitive work. Primitives base classes ----------------------- ``FileReaderPrimitiveBase``: A primitive base class for reading files referenced in columns. ``DatasetSplitPrimitiveBase``: A base class for primitives which fit on a ``Dataset`` object to produce splits of that ``Dataset`` when producing. ``TabularSplitPrimitiveBase``: A primitive base class for splitting tabular datasets. Examples -------- Examples of primitives using these base classes can be found `in this repository `__: - `DataFrameImageReaderPrimitive `__ A primitive which reads columns referencing image files. - `FixedSplitDatasetSplitPrimitive `__ A primitive which splits a tabular Dataset in a way that uses for the test (score) split a fixed list of primary index values or row indices of the main resource to be used. All other rows are added used for the train split. - `KFoldDatasetSplitPrimitive `__ A primitive which splits a tabular Dataset for k-fold cross-validation. - `KFoldTimeSeriesSplitPrimitive `__ A primitive which splits a tabular time-series Dataset for k-fold cross-validation. - `NoSplitDatasetSplitPrimitive `__ A primitive which splits a tabular Dataset in a way that for all splits it produces the same (full) Dataset. - `TrainScoreDatasetSplitPrimitive `__ A primitive which splits a tabular Dataset into random train and score subsets.