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Document Type : Latin Dissertation
Language of Document : English
Record Number : 149164
Doc. No : ET20956
Main Entry : Yu Feng
Title Proper : PG-means: Learning the Number of Clusters in Data
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : We present a novel algorithm called PG-means in this thesis. This algorithmis able to determine the number of clusters in a classical Gaussian mixture modelautomatically. PG-means uses efficient statistical hypothesis tests on one-dimensionalprojections of the data and model to determine if the examples are well representedby the model. In so doing, we apply a statistical test to the entire model a t once,not just on a per-cluster basis. We show that this method works well in difficultcases such as overlapping clusters, eccentric clusters and high dimensional clusters.PG-means also works well on non-Gaussian clusters and many true clusters. Further.the new approach provides a.
Subject : Electericl tess
: برق
electronic file name : TL44102.pdf
Title and statement of responsibility and : PG-means: Learning the Number of Clusters in Data [Thesis]
 
 
 
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