Hub
Pricing About
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Community Hub
  • francescots
  • Spaces
  • Public
  • Natural Language Processing
  • Examples
  • Categorical Variables Encoding with word2vec
WorkflowWorkflow

Handling sparse categorial variables with Word2Vec

Encoding Sparse data Embedding Nlp Pca
+1
Francescots profile image

Last edited: 

Drag & drop
Like
Download workflow
Copy short link
Workflow preview
This workflow shows how to compute word embedding on a set of categorical variables with the granularity which allows them to be used as input of predictive models. In the second part of the workflow a principal component analysis is applied to the embeddings dimensions. I kept only a portion of them which caputures most of the variation, by doing so you can monitor model complexity. Following py package required: pandas gensim numpy nltk

Used extensions & nodes

Created with KNIME Analytics Platform version 4.4.2 Note: Not all extensions may be displayed.
  • Go to item
    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

    knime
  • Go to item
    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

    knime
  • Go to item
    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

    knime
  • Go to item
    KNIME Optimization extension Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.0

    knime
  • Go to item
    KNIME Plotly Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.0

    knime
  • Go to item
    KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

    knime
  • Go to item
    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.4.2

    knime
  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