BFTree (3.7)


Class for building a best-first decision tree classifier

This class uses binary split for both nominal and numeric attributes.For missing values, the method of 'fractional' instances is used.

For more information, see:

Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ.

Jerome Friedman, Trevor Hastie, Robert Tibshirani (2000).

Additive logistic regression : A statistical view of boosting.Annals of statistics.


(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: Data Training data

Output Ports

  1. Type: Weka 3.7 Classifier Trained model

Find here

Analytics > Mining > Weka > Weka (3.7) > Classification Algorithms > trees

Make sure to have this extension installed: