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arXiv · 1412.4178

On The Sharp Threshold Interval Length of Partially Connected Random Geometric Graphs During K-Means Classification

Robert A. Murphy
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Abstract

In $K$-means classification, a set of data will form clusters, i.e. classes, if the measured distances between data points (or some common point in each class) are below a certain threshold. With the assumption that the data points are randomly generated throughout some bounded region according to a certain probability distribution, we estimate the mean number of classes to form with high probability.

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Robert A. Murphy. 2014-12-13. On The Sharp Threshold Interval Length of Partially Connected Random Geometric Graphs During K-Means Classification. https://arxiv.org/abs/1412.4178

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