recpack.postprocessing.filters.ExcludeItems
- class recpack.postprocessing.filters.ExcludeItems(items: Union[numpy._typing._array_like._SupportsArray[numpy.dtype[Any]], numpy._typing._nested_sequence._NestedSequence[numpy._typing._array_like._SupportsArray[numpy.dtype[Any]]], bool, int, float, complex, str, bytes, numpy._typing._nested_sequence._NestedSequence[Union[bool, int, float, complex, str, bytes]]])
Remove the recommendations of specified items. https://numpy.org/doc/stable/reference/typing.html#numpy.typing.ArrayLike
- Parameters
items (ArrayLike) – ArrayLike with the identifiers for items to be removed
Methods
apply
(X_pred)Process the predictions, and return the processed matrix.
apply_all
(*csr_matrices)Apply the filter to each of the matrices.
- apply(X_pred: scipy.sparse._csr.csr_matrix) scipy.sparse._csr.csr_matrix
Process the predictions, and return the processed matrix.
- Parameters
X_pred (csr_matrix) – csr_matrix to filter
- Returns
The processed csr_matrix.
- Return type
csr_matrix
- apply_all(*csr_matrices: scipy.sparse._csr.csr_matrix) List[scipy.sparse._csr.csr_matrix]
Apply the filter to each of the matrices.
- Parameters
csr_matrices (csr_matrix) – The matrices to apply the filter to.
- Returns
The list of processed csr_matrices
- Return type
List[csr_matrix]