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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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.