0.17.1 adding bottleneck as a dependency. This library is highly-recommended by Pandas, and in lifelines we see some nice performance improvements with it too. (~15% for CoxPHFitter) There was a small bug in CoxPHFitter when using batch_mode that was causing coefficients to deviate from their MLE value. This bug eluded tests, which means that it's discrepancy was less than 0.0001 difference. It's fixed now, and even more accurate tests are added. Faster CoxPHFitter._compute_likelihood_ratio_test() Fixes a Pandas performance warning in CoxTimeVaryingFitter. Performances improvements to CoxTimeVaryingFitter
Changelog 0.20.0 Starting with 0.20.0, only Python3 will be supported. Over 75% of recent installs ...
0.13.0 removes is_significant and test_result from StatisticalResult. Users can instead choose thei...
0.22.8 New features Serializing lifelines is better supported. Packages like joblib and pickle are ...
0.24.16 - 2020-07-09 New features improved algorithm choice for large Dataframes for Cox models. Sh...
0.24.0 - 2020-02-20 This version and future versions of lifelines no longer support py35. Pandas 1....
0.16.3 More CoxPHFitter performance improvements. Up to a 40% reduction vs 0.16.2 for some datasets
v0.17.2 Another round of serious performance improvements for the Cox models. Up to 2x faster for C...
0.14.1 fixed bug with using weights and strata in CoxPHFitter fixed bug in using non-integer weight...
0.25.4 - 2020-08-26 New features New baseline estimator for Cox models: piecewise Performance impro...
0.16.2 Fixed CoxTimeVaryingFitter to allow more than one variable to be stratafied Significant perf...
0.19.0 New features New regression model WeibullAFTFitter for fitting accelerated failure time mode...
New features plot_lifetimes accepts pandas Series. Bug fixes Fixed important bug in interval cens...
0.17.0 corrected behaviour in CoxPHFitter where score_ was not being refreshed on every new fit. Re...
adding robust params to CoxPHFitter's fit. This enables atleast i) using non-integer weights in the ...
0.24.6 - 2020-05-05 New features At the cost of some performance, convergence is improved in many m...
Changelog 0.20.0 Starting with 0.20.0, only Python3 will be supported. Over 75% of recent installs ...
0.13.0 removes is_significant and test_result from StatisticalResult. Users can instead choose thei...
0.22.8 New features Serializing lifelines is better supported. Packages like joblib and pickle are ...
0.24.16 - 2020-07-09 New features improved algorithm choice for large Dataframes for Cox models. Sh...
0.24.0 - 2020-02-20 This version and future versions of lifelines no longer support py35. Pandas 1....
0.16.3 More CoxPHFitter performance improvements. Up to a 40% reduction vs 0.16.2 for some datasets
v0.17.2 Another round of serious performance improvements for the Cox models. Up to 2x faster for C...
0.14.1 fixed bug with using weights and strata in CoxPHFitter fixed bug in using non-integer weight...
0.25.4 - 2020-08-26 New features New baseline estimator for Cox models: piecewise Performance impro...
0.16.2 Fixed CoxTimeVaryingFitter to allow more than one variable to be stratafied Significant perf...
0.19.0 New features New regression model WeibullAFTFitter for fitting accelerated failure time mode...
New features plot_lifetimes accepts pandas Series. Bug fixes Fixed important bug in interval cens...
0.17.0 corrected behaviour in CoxPHFitter where score_ was not being refreshed on every new fit. Re...
adding robust params to CoxPHFitter's fit. This enables atleast i) using non-integer weights in the ...
0.24.6 - 2020-05-05 New features At the cost of some performance, convergence is improved in many m...
Changelog 0.20.0 Starting with 0.20.0, only Python3 will be supported. Over 75% of recent installs ...
0.13.0 removes is_significant and test_result from StatisticalResult. Users can instead choose thei...
0.22.8 New features Serializing lifelines is better supported. Packages like joblib and pickle are ...