Individual Conditional Expectation Plot Toolbox
Lineup plot for additivity
Backfitting for Additive Models
Clustering of ICE and d-ICE curves by kmeans.
Efficient Column Standard Deviations
Efficient Numerical Derivative for Matrix (Row-wise)
Creates an object of class dice.
Creates an object of class ice.
Melt Matrix to Long Format Vector
Create a plot of a dice object.
Plotting of ice objects.
Print method for dice objects.
Print method for ice objects.
Row-wise Centering
Savitzky-Golay Filter for Matrix (Row-wise)
Summary function for dice objects.
Summary function for ice objects.
Probability Transformation
Implements Individual Conditional Expectation (ICE) plots, a tool for visualizing the model estimated by any supervised learning algorithm. ICE plots refine Friedman's partial dependence plot by graphing the functional relationship between the predicted response and a covariate of interest for individual observations. Specifically, ICE plots highlight the variation in the fitted values across the range of a covariate of interest, suggesting where and to what extent they may exist.