mvpa2.measures.winnerΒΆ
Data aggregation procedures
Functions
| feature_loser_measure() | takes loser over features |
| feature_winner_measure() | takes winner over features |
| group_sample_loser_measure([attrs]) | takes loser after meaning over attrs |
| group_sample_winner_measure([attrs]) | takes winner after meaning over attrs |
| mean_group_sample(attrs[, attrfx]) | Returns a mapper that computes the mean samples of unique sample groups. |
| sample_loser_measure() | takes loser over samples |
| sample_winner_measure() | takes winner over samples |
| vstack(datasets[, a]) | Stacks datasets vertically (appending samples). |
Classes
| ChainLearner(learners[, auto_train, force_train]) | Combines different learners into one in a chained fashion |
| ChainNode(nodes, **kwargs) | This class allows to concatenate a list of nodes into a processing chain. |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| Measure([null_dist]) | A measure computed from a Dataset |
| WinnerMeasure(axis, fx[, other_axis_prefix]) | Select a “winning” element along samples or features. |
| partial | partial(func, *args, **keywords) - new function with partial application |
