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Telecom Churn--Demonstrating kmeans++ effectiveness

Telecom Churn--Demonstrating kmeans++ effectiveness
How effective kmeans++ is--A Demo1. This example clearly shows How effective kmeans++ is in initial selection of good (random) centroids.2. Refer: https://www.geeksforgeeks.org/ml-k-means-algorithm/ for how kmeans++ works3. With kmeans++ we get very high Silhoutte Coefficients. Without using kmeans++, Silhoutte Coefficients are very low.4.See Moodle as to how Silhoutte Coefficients are calculated for each data-point: http://203.122.28.230/moodle/mod/resource/view.php?id=3813 ContactData.csvJoinonCustomerIDCallsData.xlsremove1.customerID2.Area(s)3.Phone(s)4.StateTransform1.Churn2.IntlPlan3.VMailPlanto stringmin-maxnormaliseall featuresNo of clusters: 3iterations: 500Rest: DefaultColourThree ClustersNode 101.vmail Message2.DayCharges3.IntlChargeshighest: 0.386lowest: -0.039No of clusters: 3use kmeans++ = TrueUse euclidean distno configurationchangeshighest: 0.659lowest:0.301'Winner-Cluster' toString CSV Reader Joiner Excel Reader Column Filter Number To String Normalizer k-Means Color Manager 2D/3D Scatterplot 3D ScatterPlot (Plotly) SilhouetteCoefficient SimpleKMeans (3.7) Weka ClusterAssigner (3.7) SilhouetteCoefficient Number To String How effective kmeans++ is--A Demo1. This example clearly shows How effective kmeans++ is in initial selection of good (random) centroids.2. Refer: https://www.geeksforgeeks.org/ml-k-means-algorithm/ for how kmeans++ works3. With kmeans++ we get very high Silhoutte Coefficients. Without using kmeans++, Silhoutte Coefficients are very low.4.See Moodle as to how Silhoutte Coefficients are calculated for each data-point: http://203.122.28.230/moodle/mod/resource/view.php?id=3813 ContactData.csvJoinonCustomerIDCallsData.xlsremove1.customerID2.Area(s)3.Phone(s)4.StateTransform1.Churn2.IntlPlan3.VMailPlanto stringmin-maxnormaliseall featuresNo of clusters: 3iterations: 500Rest: DefaultColourThree ClustersNode 101.vmail Message2.DayCharges3.IntlChargeshighest: 0.386lowest: -0.039No of clusters: 3use kmeans++ = TrueUse euclidean distno configurationchangeshighest: 0.659lowest:0.301'Winner-Cluster' toString CSV Reader Joiner Excel Reader Column Filter Number To String Normalizer k-Means Color Manager 2D/3D Scatterplot 3D ScatterPlot (Plotly) SilhouetteCoefficient SimpleKMeans (3.7) Weka ClusterAssigner (3.7) SilhouetteCoefficient Number To String

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Created by: Administrator
Created at: 2021-02-28
On NodePit since: 2021-11-15
Last update: 2024-11-21
Created with KNIME version: v4.3.1
Tags: kmeanskmeans++

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