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

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

A2DE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…

A2DE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…

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

Class for generating an alternating decision tree. For further options, click the 'More' - button in the dialog. All weka dialogs…

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

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

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…

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

Class for boosting a nominal class classifier using the Adaboost M1 method. For further options, click the 'More' - button in the…

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

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

Meta classifier that enhances the performance of a regression base classifier. For further options, click the 'More' - button in …

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

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

Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier. For further op…

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

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