Hub
Pricing About
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Community Hub
  • knime
  • Spaces
  • XAI Space
  • Regression
  • Custom Models
  • 03_Compute_LIMEs
WorkflowWorkflow

LIME Loop Nodes with a Custom Regression Model

LIME Machine learning interpretability Mli Explanation Instance-level explanation
+8
KNIME profile image

Last edited: 

Drag & drop
Like
Download workflow
Copy short link
Workflow preview
An XGBoost Tree Ensemble Regression model was picked, but any model and its set of Learner and Predictor nodes can be used. - Read the dataset about wines - Partition the data in train and test - Pick few test set instances rows to explain - Create local samples for each instance in the input table (LIME Loop Start) - Score the samples using the predictor node and a trained model - Compute LIMEs, that is local model-agnostic explanations by training a local GLM using the samples and extracting the weights. - Visualize them in the Composite View (Right Click > Open View)

External resources

  • LIME - Local Interpretable Model-Agnostic Explanations, Marco Tulio Ribeiro, Blog Post
  • Data Source: UCI - Wine Quality Data Set
  • Verified Components

Used extensions & nodes

Created with KNIME Analytics Platform version 4.6.1
  • Go to item
    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.1

    KNIME profile image
    knime
  • Go to item
    KNIME H2O Machine Learning Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    KNIME profile image
    knime
  • Go to item
    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.1

    KNIME profile image
    knime
  • Go to item
    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    KNIME profile image
    knime
  • Go to item
    KNIME JSON-Processing Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.1

    KNIME profile image
    knime
  • Go to item
    KNIME Machine Learning Interpretability Extension Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    KNIME profile image
    knime
  • Go to item
    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    KNIME profile image
    knime
  • Go to item
    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    KNIME profile image
    knime
  • Go to item
    KNIME XGBoost Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

    KNIME profile image
    knime
  • Go to item
    Vernalis KNIME Nodes Trusted extension

    Vernalis Research Ltd, Cambridge, UK

    Version 1.34.2

    vernalis
  1. Go to item
  2. Go to item
  3. Go to item
  4. Go to item
  5. Go to item
  6. Go to item
Loading deployments
Loading ad hoc executions

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
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