VotedPerceptron (3.7)


Implementation of the voted perceptron algorithm by Freund and Schapire

Globally replaces all missing values, and transforms nominal attributes into binary ones.

For more information, see:

Y.Freund, R.

E.Schapire: Large margin classification using the perceptron algorithm.

In: 11th Annual Conference on Computational Learning Theory, New York, NY, 209-217, 1998.

(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 > functions

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

How to install extensions