JCBA (3.7)

A Java implementation of the CBA algorithm

The classifier works with class association rules.That are association rules where exclusively one class attribute-value-pair is allowed in the consequence.

The algorithm works as a decision list classifier and has an obligatory and an optional pruning stepBoth steps can be disbaled.

If both are disbaled it works like a unpruned decision list und uses the first rule that covers a test instance for prediction.For more information see:

Bing Liu, Wynne Hsu, Yiming Ma: Integrating Classification and Association Rule Mining.

In: Fourth International Conference on Knowledge Discovery and Data Mining, 80-86, 1998.

W.Li, J.

Han, J.Pei: CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules.In: ICDM'01, 369-376, 2001.

(based on WEKA 3.7)

For further options, click the 'More' - button in the dialog.

All weka dialogs have a panel where you can specify classifier-specific parameters.

Input ports

1. Type: Table
   Training data
   Training data

Output ports

1. Type: Weka 3.7 Classifier
   Trained model
   Trained model