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  • 03_Imbalanced_Sentiment_Analysis_with_XGBoost
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Imbalanced Sentiment Analysis with XGBoost

Sentiment analysis NLP Natural Language Processing Text classification Practicing Data Science
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This workflow shows how to import text from a csv file, convert it to documents, preprocess the documents and transform them into numerical document vectors. Finally two predictive models are trained on the vectors to predict the sentiment class of the documents.

External resources

  • What's new in KNIME 4.6
  • Read more about "Lexicon-based sentiment analysis: A tutorial"
  • Sentiment Classification of Documents

Used extensions & nodes

Created with KNIME Analytics Platform version 4.6.0
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

  • Go to item
    KNIME Machine Learning Interpretability Extension Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

  • Go to item
    KNIME Statistics Nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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    KNIME Textprocessing Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

  • Go to item
    KNIME Views (Labs) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

  • Go to item
    KNIME XGBoost Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.6.0

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