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.
- Type: Data Training data
- Type: Weka 3.7 Classifier Trained model
Analytics > Mining > Weka > Weka (3.7) > Classification Algorithms > trees
Make sure to have this extension installed: