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Dimensionality Reduction with PCA w/ correlations

Scatter plot PCA Principal Component Analysis Dimensionality reduction
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This workflow applies PCA dimensionality reduction to reduce the dataset dimensions from three to two features. Data points are then displayed in a scatter plot. Normalization is included for general use. Linear and rank correlations are calculated.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.7.2
  • KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.2

    knime
  • KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime
  • KNIME Statistics Nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.7.0

    knime
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