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.
- Type: Data Training data
- Type: Weka 3.7 Classifier Trained model
Analytics > Mining > Weka > Weka (3.7) > Classification Algorithms > lazy
Make sure to have this extension installed:
KNIME Weka Data Mining Integration (3.7)
Update site for KNIME Analytics Platform 3.7:
KNIME Analytics Platform 3.7 Update Site