Integrate new version of the model that jointly models the competing risk incidences #53
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Fix TODO in survival_boost_test.py
Co-authored-by: Olivier Grisel <[email protected]>
DOC documents parameters in SurvivalBoost docstring
…ck_predict_survival_boost
…oost API change the shape of the incidence curves
DOC Use data generator in marginal cumulative incidence example
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@juAlberge @Vincent-Maladiere @judithabk6 I think this branch is in a good enough shape to be reviewed for merging.
Note: I also updated the marginal competing risk estimation example to use KM based IPCW as this example is a case of a marginal censoring mechanism. Using KM-IPCW really improves the quality of the plots on censored data. Even when tweaking the other hyper-parameters I could not get the alternating IPCW strategy to work well on this example. This will also be investigated later. |
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* survival analysis example * change the `predict_cumutive_incidence` function to `predict_survival_function` * fix the example and adapt it to sphinx * add torch to doc deps because because pycox doesn't require it * clean example --------- Co-authored-by: LeoGrin <[email protected]> Co-authored-by: Vincent Maladiere <[email protected]>
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…competing risk incidences (#53) * removing Incidence * adding MultiIncidence to hazardosu * reinserting example for multiincidence * Hardcode uniform time sampler to simplify estimator * Remove any reference to the dataset-specific oracle scorer * Rename to SurvivalBoost * Update the .score method to work in the any event setting * Rename test file * Fix test_gradient_boosting_incidence_parameter_tuning * Simplify code * Raise error if hard-zero resampling censors too many events * adding test * Refactor survival boost tests * Fix missing assertion * fix TODO * fix linter * Fix LaTeX * More informative error message for bad value for hard_zero_fraction * Remove untested code related to Cox PH based conditional censoring estimation * Avoid using 'Est' as a short hand for 'Estimator' * FIX accept both float and array-like for time_horizon in predict_proba * DOC update predict_proba docstring * TST add a test that check the behaviour of predict_proba * DOC add docstring to test * TST check that probability sum to one for all events * DOC fix docstring type for time_horizon * Rename BaseIPCW to KaplanMeierIPCW. Adding some documentation. * API correct the API of predict_proba * Use arturo formulation * Silence 'DeprecationWarning: invalid escape sequence' by using raw docstrings with LaTeX expressions * update docstring * Simplify KaplanMeierIPCW and improve its docstring * adding some documentation to SurvivalBoost * More docstring fixes * Apply suggestions from code review Co-authored-by: Olivier Grisel <[email protected]> * TST update test and code to follow scikit-learn convention * TST check that we override properly * Apply suggestions from code review Co-authored-by: Olivier Grisel <[email protected]> * DOC start documenting parameter * DOC documents parameters in SurvivalBoost docstring * DOC add ipcw estimator docstring * DOC add attributes, reference, and examples * DOC document some parameters and attributes of WeightedMultiClassTargetSampler * API change the shape of the incidence curves * DOC Use data generator in marginal cumulative incidence example * FIX slice properly the prediction * fix install instructions with flit * MAINT Remove old python version in black config (#57) * MAINT activate doctest check with pytest by default * Fix a pandas warning in load_seer * FIX do not pytest collect outside of the hazardous module folder * FIX update the example to integrate on the right columns * Apply suggestions from code review Co-authored-by: Olivier Grisel <[email protected]> * Set explicit value for n_events * Improve variable names and comments in WeightedMultiClassTargetSampler * Use n_horizons_per_observation=3 by default * Update hazardous/_survival_boost.py * Remove reference to "column" to describe the second axis of a 3D array. * Improve docstrings for SurvivalBoost * Make sure to use zero-width param ranges in marginal example * Silence AJ warning on tied events * Small improvements * Use a string in the public API of SurvivalBoost to select the censoring estimator * Keep IPCW estimator private API for now * replacing any occurence of _est to _estimator * fixing math, harmonising different notations. * Example survival analysis (#70) * survival analysis example * change the `predict_cumutive_incidence` function to `predict_survival_function` * fix the example and adapt it to sphinx * add torch to doc deps because because pycox doesn't require it * clean example --------- Co-authored-by: LeoGrin <[email protected]> Co-authored-by: Vincent Maladiere <[email protected]> * enhance documentation --------- Co-authored-by: Julie Alberge <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: ArturoAmorQ <[email protected]> Co-authored-by: Judith Abecassis <[email protected]> Co-authored-by: Jovan Stojanovic <[email protected]> Co-authored-by: Julie <[email protected]> Co-authored-by: LeoGrin <[email protected]> Co-authored-by: Vincent Maladiere <[email protected]> 5e581d5
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This involves renaming the model class to
SurvivalBoostas a short and easy to remember name.