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KPCA

Kernel Principal Component Analysis
IRIS Dataset with KPCA vs normal PCA Random Dataset with KPCA This workflow calculates de KPCA using kernlab R package KPCANode 758Predict KPCAirisNode 762Node 763KPCA PlotNode 765Node 766Node 767Node 768PCA Ploteigen valuesNode 771Node 773Node 774eigen valuesNode 776Node 777KPCANode 780Node 781Predict KPCANode 783With 1000 obs runs okwith 10000 obs took 30 minNumber todimensions k=2Number todimensions k=2 R Learner Column Filter R Predictor R Source (Table) Joiner Color Manager Scatter Plot(local) PCA Compute PCA Apply Color Appender Joiner Scatter Plot(local) R Snippet Extract TableDimension Table Column toVariable (deprecated) Extract TableDimension R Snippet Scatter Plot(local) Table Column toVariable (deprecated) R Learner Joiner Column Filter R Predictor Color Manager Data Generator Integer Input Integer Input IRIS Dataset with KPCA vs normal PCA Random Dataset with KPCA This workflow calculates de KPCA using kernlab R package KPCANode 758Predict KPCAirisNode 762Node 763KPCA PlotNode 765Node 766Node 767Node 768PCA Ploteigen valuesNode 771Node 773Node 774eigen valuesNode 776Node 777KPCANode 780Node 781Predict KPCANode 783With 1000 obs runs okwith 10000 obs took 30 minNumber todimensions k=2Number todimensions k=2R Learner Column Filter R Predictor R Source (Table) Joiner Color Manager Scatter Plot(local) PCA Compute PCA Apply Color Appender Joiner Scatter Plot(local) R Snippet Extract TableDimension Table Column toVariable (deprecated) Extract TableDimension R Snippet Scatter Plot(local) Table Column toVariable (deprecated) R Learner Joiner Column Filter R Predictor Color Manager Data Generator Integer Input Integer Input

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: Mauricio Salazar
Created at: 2019-09-24
On NodePit since: 2020-12-28
Last update: 2024-04-26
Created with KNIME version: v4.3.0
Tags: KPCAdimensionality reduction

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