Comments (5)
sebp
commented on June 30, 2024
Currently, only Python 3.4 is fully supported on Windows due to cvxopt/cvxopt#94, therefore I haven't checked other versions. If I find some time, I'll try to create a Windows build with cxvopt support disabled.
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scienceML
commented on June 30, 2024
Thank you - looking forward to it
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scienceML
commented on June 30, 2024
Based on the description it is only for Linux and Mac - please confirm
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sebp
commented on June 30, 2024
I was able to create a window build for Python 3.5 and 3.6 without cvxopt support.
I didn't encounter the error you encountered, it might be related to using VS 2012 instead of VS 2015, which is needed for Python 3.5 and 3.6.
Could you please try whether the pre-built Windows package from https://ci.appveyor.com/project/sebp/scikit-survival/build/job/81y016cbeunhhw20/artifacts works for you?
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scienceML
commented on June 30, 2024
Fantastic sebp - after installing vs2015 and running your exe, python code recognize FastKernelSurvivalSVM and others. thank you!
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Related Issues (20)
- Visualizing decision trees HOT 1
- Survival Random Forest predict_survival_function does not scale with `n_jobs` HOT 1
- Clarify which metrics expect output of survival function vs output of cumulative hazard function HOT 1
- conf_type is not working in kaplan_meier_estimator: HOT 2
- How to ensemble predictions from ExtraSurvivalTrees models? HOT 1
- parallelization for GradientBoostingSurvivalAnalysis? HOT 1
- plotting a tree from estimators_[i] from RandomSurvivalForest.fit() HOT 6
- Possible memory leak for FastKernelSurvivalSVM HOT 1
- Fit does not throw exception if negative event times are passed
- Description of estimate parameter in integrated_brier_score is unclear HOT 1
- Ipcw estimation: Add small value for numerical stability HOT 1
- Description of estimate parameter in brier_score is unclear HOT 4
- Ability to suppress future warnings? HOT 1
- Possible improvement in documentation of Cumulative dynamic AUC HOT 1
- concordance_index_ipcw output inconsistent with survAUC package HOT 1
- Support Scikit-Learn 1.4 (stable version)
- 'cosine' kernel in FastKernelSurvivalSVM still in documentation but not working in 0.22.2
- Can't instantiate abstract class GradientBoostingSurvivalAnalysis with abstract methods _encode_y, _get_loss HOT 1
- SurvivalTree is handling sample_weight incorrectly
- [BUG] `GradientBoostingSurvivalAnalysis` - docstring/logic mismatch on possible `criterion` values HOT 1
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