lifelines 0.24.0

v0.24.0

on Python PyPI

0.24.0 - 2020-02-20

This version and future versions of lifelines no longer support py35. Pandas 1.0 is fully supported, along with previous version. Minimum Scipy has been bumped to 1.2.0

New features

• CoxPHFitter and CoxTimeVaryingFitter has support for an elastic net penalty, which includes L1 and L2 regression.
• CoxPHFitter has new baseline survival estimation methods. Specifically, spline now estimates the coefficients and baseline survival using splines. The traditional method, breslow, is still the default however.
• Regression models have a new score method that will score your model against a dataset (ex: a testing or validation dataset). The default is to evaluate the log-likelihood, but also the concordance index can be chose.
• New MixtureCureFitter for quickly creating univariate mixture models.
• Univariate parametric models have a plot_density, density_at_times, and property density_ that computes the probability density function estimates.
• new dataset for interval regression involving C. Botulinum.
• new lifelines.fitters.mixins.ProportionalHazardMixin that implements proportional hazard checks.

API Changes

• Models' prediction method that return a single array now return a Series (use to return a DataFrame). This includes predict_median, predict_percentile, predict_expectation, predict_log_partial_hazard, and possibly others.
• The penalty in Cox models is now scaled by the number of observations. This makes it invariant to changing sample sizes. This change also make the penalty magnitude behave the same as any parametric regression model.
• score_ on models has been renamed concordance_index_
• models' .variance_matrix_ is now a DataFrame.
• CoxTimeVaryingFitter no longer requires an id_col. It's optional, and some checks may be done for integrity if provided.
• Significant changes to utils.k_fold_cross_validation.
• removed automatically adding inf from PiecewiseExponentialRegressionFitter.breakpoints and PiecewiseExponentialFitter.breakpoints
• tie_method was dropped from Cox models (it was always Efron anyways...)
• Mixins are moved to lifelines.fitters.mixins
• find_best_parametric_model evaluation kwarg has been changed to scoring_method.
• removed _score_ and path from Cox model.

Bug fixes

• Fixed show_censors with KaplanMeierFitter.plot_cumulative_density see issue #940.
• Fixed error in "BIC" code path in find_best_parametric_model
• Fixed a bug where left censoring in AFT models was not converging well
• Cox models now incorporate any penalizers in their log_likelihood_