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  • 03_Backward_Feature_Elimination
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Backward Feature Elimination

ETL Accuracy Classification Dimensionality reduction Backward feature elimination
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This workflow shows the implementation of the backward feature elimination procedure via the Backward Feature Elimnation metanode. Inside the metanode you will find a loop extracting a subset of the input columns at each iteration according to the backeward feature elimination procedure. The last node is the Backward Feature Elimination Filtering and allows to select the feature set and the corresponding accuracy.

External resources

  • Principal component analysis
  • Neural networks [6.1] : Autoencoder - definition
  • Linear discriminant analysis
  • Paper Dissected: "Visualizing Data Using t-SNE" Explained
  • Random Forest for Data Dimensionality Reduction
  • Seven Techniques for Data Dimensionality Reduction
  • KDD Cup 2009 Data

Used extensions & nodes

Created with KNIME Analytics Platform version 4.7.0
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Versions 4.3.1, 4.7.0

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