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AutoML_​Clustering_​K-Means

Simple AutoML Clustering for K-Means
optimizing kbetween 3 and 6default: iris dataset(3 classes of flowers)(optionally) Right Click > Execute and Open Viewapplying best cluster modelfound on partitioned dataconfigured on Iris datasetRight Click > Execute and Open Viewk-meansdoes not supportmissing valuesOptimized K-Means(Silhouette Coefficient) ExtractColumn Header Insert ColumnHeader Transpose Data Access View Partitioning Cluster Assigner Results Dashboard Missing Value optimizing kbetween 3 and 6default: iris dataset(3 classes of flowers)(optionally) Right Click > Execute and Open Viewapplying best cluster modelfound on partitioned dataconfigured on Iris datasetRight Click > Execute and Open Viewk-meansdoes not supportmissing valuesOptimized K-Means(Silhouette Coefficient) ExtractColumn Header Insert ColumnHeader Transpose Data Access View Partitioning Cluster Assigner Results Dashboard Missing Value

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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: paolotamag
Created at: 2020-12-15
On NodePit since: 2020-12-15
Last update: 2024-04-18
Created with KNIME version: v4.3.0
Tags: SilhouetteK-MeansAutoML

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