cito 1.1

New features

• hyperparameter tuning (experimental)
• burnin parameter
• multivariate probit model
• X and Y support (alternative interface)
• negative binomial distribution

Minor changes

• Improved vignette
• Improved README

Bug fixes

• dropout is turned off after training (into evaluation mode)
• predict type was changed
• small bug in the activation functions
• extended support for mps devices

cito 1.0.2

New features

• conditional Effects (approximate linear effects)
• uncertainties via bootstrapping (can be forwarded to all functions)
• summary() can return standard errors and p-values for xAI metrics
• improved documentation / several new vignettes
• baseline loss
• loss = inf/na is not captured, training is aborted and user will be warned
• mps (M1/M2 gpu) device is now supported

Bug fixes

• early stopping (ignored validation loss)
• weights are only saved for best and last epoch
• gaussian likelihood works now properly
• reguarlization loss is not visualized
• reduce lr on plateau works now with validation loss

cito 1.0.1

New features

• predict function can now return directly the class
• custom loss and parameter can now also be optimized
• summary function (importances) does now support loss = binomial

Minor changes

• print of summary is now more clear

Bug fixes

• in ALE function providing new data did not work properly
• Performance improvements with new dataloader
• ALE/PDP work now correctly for softmax
• PDP ICE return now correct curves
• Early stopping works now
• lr reducer on plateau didn’t reduce lr
• Predictions are now made on cuda of the model is stored on cuda