Hub
Pricing About
WorkflowWorkflow

Multivariate Time Series Analysis with an RNN - Training

Time seriesDeep learningRNNLSTMMultivariate time series
+1
T1
Draft Latest edits on 
Oct 13, 2020 12:00 PM
Drag & drop
Like
Download workflow
Workflow preview
This is a simple example workflow for multivariant time series analysis using an LSTM based recurrent neural network and implemented via the KNIME Deep Learning - Keras Integration. It is based on the bike demand predition dataset from Kaggle and trains a model to predict the demand in the next hour based on the demand and the other features in the last 10 hours.

External resources

  • Dataset on Kaggle
Loading deploymentsLoading ad hoc jobs

Used extensions & nodes

Created with KNIME Analytics Platform version 4.7.1
  • Go to item
    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.1

    knime
  • Go to item
    KNIME Data GenerationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime
  • Go to item
    KNIME Deep Learning - Keras IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime
  • Go to item
    KNIME Excel SupportTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

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

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime
  • Go to item
    KNIME PlotlyTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime

Legal

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

KNIME
Open for Innovation

KNIME AG
Talacker 50
8001 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • Courses + Certification
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more about KNIME Business Hub
© 2025 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Data Processing Agreement
  • Credits