New features - `keras_joint_mae_tilted_loss`: to fit the median in quantile regression (use average_type='median' in SamQuantileMLP) - `plot_feature_importances`: bar plot of feature importances (e.g. computed in SamQuantileMLP.quantile_feature_importances - `compute_quantile_ratios`: to check the proportion of data falling beneath certain quantile
2.0.21
Bugfixed - eli5 uses the sklearn.metrics.scorer module, which is gone in 0.24.0, so we need <=0.24.0 - shap does not work with tensorflow 2.4.0 so we need <=2.3.1
2.0.20
Bugfixed - statsmodels is no longer a dependency (dependency introduced in version 2.0.19)
2.0.19
New features - `sam.metrics.tilted_loss`: A tilted loss function that works with numpy / pandas - `sam.models.LinearQuantileRegression`: sklearn style wrapper for quantile regression using statsmodels
2.0.18
Changes - `sam.models.SamQuantileMLP`: Now stores the input columns (before featurebuilding) which can be accessed by `get_input_cols()`
2.0.17
Changes - `sam.validation.flatline`: Now accepts `window="auto"` option, for which the maximum flatline window is estimated in the `fit` method