Icon

ApplicationIris_​UnlabeledTruth

Clustering on the Iris data
True clusters K-means Hierarchical clustering DBSCAN Readingthe irisdataK-meansclustering withk=3Normalize numerical attributesDe-normalizeback to theoriginal scaleAssign colors todifferent clustersScatter plotwith clustersfrom K-meansAverage linkagek=3De-normalizeback to theoriginal scaleAssign colors todifferent clustersScatter plotwith clustersfrom hierarchicalEpsilon=0.25MinPts=3De-normalizeback to theoriginal scaleAssign colors todifferent clustersScatter plotwith clustersfrom DBSCANDistancecalculationScatter plotwithout labels Table Reader k-Means Normalizer Denormalizer Color Manager Scatter Plot HierarchicalClustering Denormalizer Color Manager Scatter Plot DBSCAN Denormalizer Color Manager Scatter Plot Numeric Distances Scatter Plot True clusters K-means Hierarchical clustering DBSCAN Readingthe irisdataK-meansclustering withk=3Normalize numerical attributesDe-normalizeback to theoriginal scaleAssign colors todifferent clustersScatter plotwith clustersfrom K-meansAverage linkagek=3De-normalizeback to theoriginal scaleAssign colors todifferent clustersScatter plotwith clustersfrom hierarchicalEpsilon=0.25MinPts=3De-normalizeback to theoriginal scaleAssign colors todifferent clustersScatter plotwith clustersfrom DBSCANDistancecalculationScatter plotwithout labelsTable Reader k-Means Normalizer Denormalizer Color Manager Scatter Plot HierarchicalClustering Denormalizer Color Manager Scatter Plot DBSCAN Denormalizer Color Manager Scatter Plot Numeric Distances Scatter Plot

Nodes

Extensions

Links

Download

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

Download Workflow
Created by: Satoru
Created at: 2021-05-14
On NodePit since: 2021-11-15
Last update: 2024-11-21
Created with KNIME version: v4.3.3
Tags: K-meansHierarchical clusteringDBSCAN

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!