Hub
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Hub
  • knime
  • Spaces
  • Academic Alliance
  • Guide to Intelligent Data Science
  • Example Workflows
  • Chapter5
  • 01_CrossValidation_Scorer_ROC
WorkflowWorkflow

Training and Testing a Model (decision tree)

TheGuideBook Decision tree Testing Training Cross-validation
+9

Last edited: 

Drag & drop
Like
Download workflow
Copy short link
Workflow preview
This workflow shows how to train and test a basic classification model. Using the adult dataset, a decision tree is trained and tested to predict the "income" class column. Testing is obtained via simple accuracy measures via the Scorer node, the ROC curve, and a Cross Validation loop.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.3.1
  • Go to item
    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

  • Go to item
    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  1. Go to item
  2. Go to item
  3. Go to item
  4. Go to item
  5. Go to item
  6. Go to item

Legal

By using or downloading the workflow, you agree to our terms and conditions.

Discussion
Discussions are currently not available, please try again later.

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