Support Vector Machines with Class Weights

Support Vector Machines with Spectrum String Kernel

Tree Augmented Naive Bayes Classifier Structure Learner Wrapper

Variational Bayesian Multinomial Probit Regression

Adjacent Categories Probability Model for Ordinal Data

Continuation Ratio Model for Ordinal Data

Cumulative Probability Model for Ordinal Data

As of version 3.0.0 of the kohonen package, the argument `user.weights` replaces the old `alpha` parameter. `user.weights` is usually a vector of relative weights such as `c(1, 3)` but is parameterized here as a proportion such as `c(1-.75, .75)` where the .75 is the value of the tuning parameter passed to `train` and indicates that the outcome layer has 3 times the weight as the predictor layer.