Changes in version 1.4.0: o Weighted voting mode that uses the distance from an observation to the nearest crossover point of the class densities added. o Bartlett Test selection function included. o New class SelectResult. rankPlot and selectionPlot can additionally work with lists of SelectResult objects. All feature selection functions now return a SelectResult object or a list of them. o priorSelection is a new selection function for using features selected in a prior cross validation for a new dataset classification. o New weighted voting mode, where the weight is the distance of the x value from the nearest crossover point of the two densities. Useful for predictions with skewed features. Changes in version 1.2.0: o More classification flexibility, now with parameter tuning integrated into the process. o New performance evaluation functions, such as a ROC curve and a performance plot. o Some existing predictor functions are able to return class scores, not just class labels. Changes in version 1.0.0: o First release of the package, which allows parallelised and customised classification, with many convenient performance evaluation functions.