Class implementing an Apriori-type algorithm. Iteratively reduces the minimum support until it finds the required number of rules…

DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examp…

Class for building and using a 0-R classifier. Predicts the mean (for a numeric class) or the mode (for a nominal class). (based …

Class for performing parameter selection by cross-validation for any classifier. For more information, see: R. Kohavi (1995). Wra…

Class for constructing an unpruned decision tree based on the ID3 algorithm. Can only deal with nominal attributes. No missing va…

Implementation of the voted perceptron algorithm by Freund and Schapire. Globally replaces all missing values, and transforms nom…

Class for building and using a Complement class Naive Bayes classifier. For more information see, Jason D. Rennie, Lawrence Shih,…

Class for performing additive logistic regression. This class performs classification using a regression scheme as the base learn…

M5Base. Implements base routines for generating M5 Model trees and rules The original algorithm M5 was invented by R. Quinlan and…

Implements Bayesian Logistic Regression for both Gaussian and Laplace Priors. For more information, see Alexander Genkin, David D…

A metaclassifier for handling multi-class datasets with 2-class classifiers. This classifier is also capable of applying error co…

Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. Like the classifier, the stru…

Yiling Yang, Xudong Guan, Jinyuan You: CLOPE: a fast and effective clustering algorithm for transactional data. In: Proceedings o…

Class for building and using a multinomial logistic regression model with a ridge estimator. There are some modifications, howeve…

Class for running an arbitrary associator on data that has been passed through an arbitrary filter. Like the associator, the stru…

Class for using linear regression for prediction. Uses the Akaike criterion for model selection, and is able to deal with weighte…

Generates a decision list for regression problems using separate-and-conquer. In each iteration it builds a model tree using M5 a…

Cluster data using the sequential information bottleneck algorithm. Note: only hard clustering scheme is supported. sIB assign fo…

Class for construction a Rotation Forest. Can do classification and regression depending on the base learner. For more informatio…

A metaclassifier that selecting a mid-point threshold on the probability output by a Classifier. The midpoint threshold is set so…