LWL (3.7)

Locally weighted learning

Uses an instance-based algorithm to assign instance weights which are then used by a specified WeightedInstancesHandler.Can do classification (e.g.

using naive Bayes) or regression (e.g.using linear regression).

For more info, see

Eibe Frank, Mark Hall, Bernhard Pfahringer: Locally Weighted Naive Bayes.

In: 19th Conference in Uncertainty in Artificial Intelligence, 249-256, 2003.

C. Atkeson, A. Moore, S. Schaal (1996). Locally weighted learning. AI Review..

(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