Hub
Pricing About
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Community Hub
  • Nodes
  • RBFNetwork (3.6)
NodeNode / Learner

RBFNetwork (3.6)

Analytics Integrations Weka Weka (3.6) Classification Algorithms
+1
Drag & drop
Like
Copy short link

Class that implements a normalized Gaussian radial basisbasis function network. It uses the k-means clustering algorithm to provide the basis functions and learns either a logistic regression (discrete class problems) or linear regression (numeric class problems) on top of that. Symmetric multivariate Gaussians are fit to the data from each cluster. If the class is nominal it uses the given number of clusters per class.It standardizes all numeric attributes to zero mean and unit variance.

(based on WEKA 3.6)

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 3.6 Classifier
    Trained classifier
    Trained classifier

Extension

The RBFNetwork (3.6) 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

No known nodes available

KNIME
Open for Innovation

KNIME AG
Talacker 50
8001 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • E-Learning course
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • KNIME Open Source Story
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more on KNIME Business Hub
© 2023 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Credits