[ENH] adapter from scipy rv_discrete to skpro Empirical
#155
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fkiraly
added
enhancement
module:probability&simulation
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #155 +/- ##
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+ Coverage 64.09% 64.62% +0.52%
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Files 104 107 +3
Lines 5587 5636 +49
Branches 1047 1054 +7
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+ Hits 3581 3642 +61
+ Misses 1720 1712 -8
+ Partials 286 282 -4 ☔ View full report in Codecov by Sentry. |
fkiraly
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Jan 30, 2024
…PH model (#157) This PR implements framework support for survival (aka time-to-event or failure time) prediction, adds tests, and an interface to `statsmodels` cox proportional hazards models as test case. Depends on #155 and #159 which should be merged first. ### Design Survival prediction models use the current `BaseRegressorProba` base class, which has `fit` extended to take a third argument `C`, a dataframe-like with a censoring indicator. Regressors capable of making use of the third argument `C` are identified via the `capability:survival` tag (being `True`). Regressors without this tag also take `C` but ignore it, corresponding to the "ignore censoring" reduction strategy. This way, all existing regressors can be used for survival prediction and vice versa. The interface is also fully downwards compatible for users - `C` defaults to `None` - and for extenders - estimators without the tag do not assume a `C` present in fit, as in this case only `X_inner`, `y_inner` are passed in `fit`. As the `predict` and `predict_proba` interfaces remain unchanged, metrics do not need to be adapted, they directly work. To avoid cluttering the docs for users who are interested primarily in probabilistic regression without censoring, models with the `capability:survival` tag have a more detailed `fit` docstring. The difference is mediated via a base class `BaseSuvReg`, which is the same as `BaseRegressorProba` with docstring overrides. ### Testing As time-to-event models inherit from `BaseProbaRegressor`, the existing `TestAllRegressors` suite tests runs on all survival prediction models. A scenario with a non-trivial `C` is added. As regressors and time-to-event models have an interchangeable interface (see above), both are tested with non-trivial `C`, with `C=None`, and without a `C` being passed. ### Further contents * an inteface to `statsmodels` proportional hazards models, `skpro.survival.coxph.CoxPH`, to showcase and test the interface * `Pipeline` is updated to accommodate survival models, for this the tag needs to be carried and `C` passed through in `_fit` * update to the API reference - new page for survival prediction * survival prediction extension template
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This PR adds an adapter from lists of
scipyrv_discretetoskproEmpirical.This adapter will be useful in interfacing
statsmodelsmodels that return lists of discreterv_discretedistributions to represent tabular distribution objects.Also makes minor corrections to the
Empiricaldocstring, and removes a stray line.