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.
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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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