Class for generating an alternating decision tree. The basic algorithm is based on: Freund, Y., Mason, L.: The alternating decisi…

AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…

AODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification ti…

Class for boosting a nominal class classifier using the Adaboost M1 method. Only nominal class problems can be tackled. Often dra…

Meta classifier that enhances the performance of a regression base classifier. Each iteration fits a model to the residuals left …

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

Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier. (based on WEKA…

Class for building a best-first decision tree classifier. This class uses binary split for both nominal and numeric attributes. F…

Class for bagging a classifier to reduce variance. Can do classification and regression depending on the base learner. For more i…

Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier. Provides …

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

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

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

A meta classifier for handling multi-class datasets with 2-class classifiers by building a random class-balanced tree structure. …

A simple meta-classifier that uses a clusterer for classification. For cluster algorithms that use a fixed number of clusterers, …

Class for doing classification using regression methods. Class is binarized and one regression model is built for each class valu…

Class implementing the Cobweb and Classit clustering algorithms. Note: the application of node operators (merging, splitting etc.…

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

This class implements a single conjunctive rule learner* that can predict for numeric and nominal class labels. A rule consists o…

A metaclassifier that makes its base classifier cost-sensitive. Two methods can be used to introduce cost-sensitivity: reweightin…