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ElbowMethod

Elbow Method

Elbow method to determine the number of clusters, applied to simulated data with 6 clusters.

Plot of total within cluster squared distances (toy data) adding cluster centercolumnsRenumbering rowsCollect Wkfrom different kNormalize numerical attributesCalculating squareddistance fromcentroidwith Java SnippetRenumbering rowsLoop over kCombiningk and WkPlotting Wk vs kLoadingtoy datak-Means Joiner (deprecated) RowID Loop End(deprecated) Normalizer k-table CalculateSquaredDist RowID Table Row To VariableLoop Start (deprecated) Column Appender Line Plot Table Reader(deprecated) Plot of total within cluster squared distances (toy data) adding cluster centercolumnsRenumbering rowsCollect Wkfrom different kNormalize numerical attributesCalculating squareddistance fromcentroidwith Java SnippetRenumbering rowsLoop over kCombiningk and WkPlotting Wk vs kLoadingtoy datak-Means Joiner (deprecated) RowID Loop End(deprecated) Normalizer k-table CalculateSquaredDist RowID Table Row To VariableLoop Start (deprecated) Column Appender Line Plot Table Reader(deprecated)

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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: Satoru
Created at: 2020-11-19
On NodePit since: 2022-12-08
Last update: 2024-04-27
Created with KNIME version: v4.6.3
Tags: elbow methodk-meansclustering

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