Hub
Pricing About
NodeNode / Learner

VotedPerceptron (3.7)

AnalyticsIntegrationsWekaWeka (3.7)Classification Algorithms
+1
Drag & drop
Like

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.

Node details

Input ports
  1. Type: Table
    Training data
    Training data
Output ports
  1. Type: Weka 3.7 Classifier
    Trained model
    Trained model

Extension

The VotedPerceptron (3.7) node is part of this extension:

  1. Go to item

Related workflows & nodes

  1. Go to item
  2. Go to item
  3. Go to item

KNIME
Open for Innovation

KNIME AG
Talacker 50
8001 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • Courses + Certification
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more about KNIME Business Hub
© 2025 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Data Processing Agreement
  • Credits