K-Means Project

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PROJECT TITLE: K-Means Clustering

PURPOSE OF PROJECT: Implement k-means clustering on a training data set to predict classification values of a test data set.

AUTHORS: Dhanamjay

VERSION or DATE: 1.0 14/08/2014

INSTRUCTIONS: 1) Compile both Java files
(javac Data.java KMeansClustering.java)
2) Run KMeansClustering (java KMeansClustering)
3) After prompted, specify number of centroids to use.
The experiment intended to classify test data values using the data
mining strategy known as k-means clustering.

The 6 variables in the training data are used to plot the data and centroids are placed to locate clumps of the 255, classified training data. Once located, a classification value can be assigned to the 100, test data.

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