skdatasets.utils.scores.hypotheses_table

skdatasets.utils.scores.hypotheses_table(samples: Union[_SupportsArray[dtype], _NestedSequence[_SupportsArray[dtype]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]], models: Sequence[str], *, alpha: float = 0.05, multitest: Optional[Literal['kruskal', 'friedmanchisquare']] = None, test: Literal['mannwhitneyu', 'wilcoxon'] = 'wilcoxon', correction: Optional[Literal[None, 'bonferroni', 'sidak', 'holm-sidak', 'holm', 'simes-hochberg', 'hommel', 'fdr_bh', 'fdr_by', 'fdr_tsbh', 'fdr_tsbky']] = None, multitest_args: Optional[Mapping[str, Any]] = None, test_args: Optional[Mapping[str, Any]] = None) → Tuple[Optional[DataFrame], Optional[DataFrame]][source]

Hypotheses table.

Prints a hypothesis table with a selected test and correction.

Parameters:

  • samples (array-like) – Matrix of samples where each column represent a model.

  • models (array-like) – Model names.

  • alpha (float in [0, 1], default=0.05) – Significance level.

  • multitest ({'kruskal', 'friedmanchisquare'}, default=None) – Ranking multitest used.

  • test ({'mannwhitneyu', 'wilcoxon'}, default='wilcoxon') – Ranking test used.

  • correction ({'bonferroni', 'sidak', 'holm-sidak', 'holm', 'simes-hochberg', 'hommel', 'fdr_bh', 'fdr_by', 'fdr_tsbh', 'fdr_tsbky'}, default=None) – Method used to adjust the p-values.

  • multitest_args (dict) – Optional ranking test arguments.

  • test_args (dict) – Optional ranking test arguments.

Returns:

  • multitest_table (array-like) – Table of p-value and rejection/non-rejection for the multitest hypothesis.

  • test_table (array-like) – Table of p-values and rejection/non-rejection for each test hypothesis.