Hub
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Hub
  • Nodes
  • Prediction Fusion
NodeNode / Predictor

Prediction Fusion

Analytics Mining Ensemble Learning Streamable
Drag & drop
Like
Copy short link

Fuses multiple prediction confidences into one, combined prediction, using the selected fusion method. The selected fusion method will be applied to all confidence values (resulting from multiple predictions) of the same class. After the fusion method was applied, the resulting combined prediction confidences will be normalized to add up to one, such that they can be interpreted as probabilities.

Note: Missing values will be skipped.

Node details

Input ports
  1. Type: Table
    Original predictions
    Table containing the predictions.
Output ports
  1. Type: Table
    Fused predictions
    Table containing the fused prediction confidences and the winning class.

Extension

The Prediction Fusion node is part of this extension:

  1. Go to item

Related workflows & nodes

  1. Go to item
    How to use the Prediction Fusion node
    This workflow shows how the prediction fusion node can be used to combine the predictions…
    knime > Examples > 04_Analytics > 13_Meta_Learning > 01_Combining_Classifiers_using_Prediction_Fusion
  2. Go to item
    Will they blend? An Ensemble model from R, Python, and KNIME models
    Will they blend Python R
    +1
    The challenge is to blend together models from different analytics platforms - i.e. Pytho…
    knime > Examples > 04_Analytics > 13_Meta_Learning > 04_Cross-Platform_Ensemble_Model
  3. Go to item
    Analytics - Model Selection to Predict Flight Departure Delays
    Data science Machine learning Model selection
    +4
    This workflow trains a number of data analytics models and automatically selects the best…
    knime > Examples > 50_Applications > 28_Predicting_Departure_Delays > 01_Analytics
  1. Go to item
  2. Go to item
  3. Go to item
  4. Go to item
  5. Go to item
  6. Go to item

KNIME
Open for Innovation

KNIME AG
Hardturmstrasse 66
8005 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 Server
© 2022 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Credits