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20210616 Pikairos K-Means followed by Hierarchical Cluster Asigner

K-Means followed by Hierarchical Clustering

This workflow clusters the iris dataset using K-Means + Hierarchical Clustering


Clustering the iris datasetusing K-Means Hierarchical Clustering Load irisdataZ-scorenormalizationInteractive view toselect the tresholdGroup intothree clusterscomplete linkageDistance matrix from K-Mean vectorsfor hierarchical clusteringeuclidean distancevisualizedendrogram21 K-Meansjust for thisdummy exampleJoin by RowID (1st input port)from HCA& Cluster Column (2nd input port)from K-meansAfter joiningyou get herefor every initial rowthe K-means clustering columnfollowed by the Hierarchical Tree Clustering columnWould you need to havethe initial data before normalizationthen use this 2nd optionJoin by RowID (1st input port)from HCA& Cluster Column (2nd input port)from K-meansConserve Initial RowIDin an extra columnfor later useConserve Initial RowIDin an extra columnfor later useAfter joiningyou get herefor every initial rowthe K-means clustering columnfollowed by the Hierarchical Tree Clustering columnTable Reader(deprecated) Normalizer HierarchicalCluster Assigner Hierarchical Clustering(DistMatrix) Distance MatrixCalculate HierarchicalCluster View k-Means Joiner (deprecated) InteractiveTable (local) Joiner (deprecated) RowID RowID InteractiveTable (local) Clustering the iris datasetusing K-Means Hierarchical Clustering Load irisdataZ-scorenormalizationInteractive view toselect the tresholdGroup intothree clusterscomplete linkageDistance matrix from K-Mean vectorsfor hierarchical clusteringeuclidean distancevisualizedendrogram21 K-Meansjust for thisdummy exampleJoin by RowID (1st input port)from HCA& Cluster Column (2nd input port)from K-meansAfter joiningyou get herefor every initial rowthe K-means clustering columnfollowed by the Hierarchical Tree Clustering columnWould you need to havethe initial data before normalizationthen use this 2nd optionJoin by RowID (1st input port)from HCA& Cluster Column (2nd input port)from K-meansConserve Initial RowIDin an extra columnfor later useConserve Initial RowIDin an extra columnfor later useAfter joiningyou get herefor every initial rowthe K-means clustering columnfollowed by the Hierarchical Tree Clustering columnTable Reader(deprecated) Normalizer HierarchicalCluster Assigner Hierarchical Clustering(DistMatrix) Distance MatrixCalculate HierarchicalCluster View k-Means Joiner (deprecated) InteractiveTable (local) Joiner (deprecated) RowID RowID InteractiveTable (local)

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Created by: Adrian Nembach
Created at: 2016-05-19
On NodePit since: 2023-02-28
Last update: 2024-12-17
Created with KNIME version: v4.4.1
Tags: clusteringmachine learningdata mininghierarchical clusteringK-Means

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