rankings_from_matrix
heterogeneity.rankings_from_matrix(matrix, polarity)
Turn a method by dataset score matrix into a per-dataset ranking matrix.
Each dataset (a column) becomes one ranking of the methods: rank 1 is the best method on that dataset, ties share a rank (competition ranking), and a method with a missing score is left out of that dataset’s ranking, encoded as 0 in the PlackettLuce convention. “Best” is resolved through the metric polarity.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
matrix |
np.ndarray | Array of shape (n_methods, n_datasets) for one metric. |
required |
polarity |
str | "higher_is_better" or "lower_is_better". |
required |
Returns
| Type | Description |
|---|---|
| numpy.ndarray | Integer array of shape (n_datasets, n_methods) with rank 1 for the best method, ties shared, and 0 for a method absent from that ranking. |
Raises
| Type | Description |
|---|---|
| ValueError | If matrix is not 2D, has fewer than two methods, or polarity is not recognised. |