Classifier for building linear logistic regression models
LogitBoost with simple regression functions as base learners is used for fitting the logistic models.The optimal number of LogitBoost iterations to perform is cross-validated, which leads to automatic attribute selection.
For more information see:Niels Landwehr, Mark Hall, Eibe Frank (2005). Logistic Model Trees.
Marc Sumner, Eibe Frank, Mark Hall: Speeding up Logistic Model Tree Induction.
In: 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, 675-683, 2005.
(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