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App Description

K-means clustering partitions data into k mutually exclusive clusters, and returns the index of the cluster to which it has assigned each observation.

K-means clustering is popular for cluster analysis in data mining. K-Means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean.

The K-Means Clustering Ipad app provides a tap method entry of 1-20 data points with a selection of 1-5 Clusters for the allocation of the data points. This app also provides the summary of the Cluster/Data Points with assigned PointX/PointY values and a calculation of the Center Point for each cluster.

The K-Means Clustering app displays the Clusters/Data Points with a color coding methodology for each data point.

A Data Entry component which provides for the manual entry of [x,y] Data Points and a results Data Table which displays the [x,y] Data Points and the computed cluster for the Data Points.

iPhone Screenshots

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K-Means Clustering screenshot 1 K-Means Clustering screenshot 2 K-Means Clustering screenshot 3 K-Means Clustering screenshot 4 K-Means Clustering screenshot 5

iPad Screenshots

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K-Means Clustering screenshot 6 K-Means Clustering screenshot 7 K-Means Clustering screenshot 8 K-Means Clustering screenshot 9 K-Means Clustering screenshot 10

App Changes

  • November 04, 2014 Initial release
  • March 13, 2015 New version 1.1
  • November 08, 2016 New version 1.2
  • June 15, 2019 New version 1.3
  • January 21, 2020 New version 1.4
  • October 27, 2020 New version 1.5

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