A Clustering and Principal Component Approach to Exemplar Based Machine Learning for Classification Identification

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" A Clustering and Principal Component Approach to Exemplar Based Machine Learning for Classification Identification "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	148806
Doc. No	:	ET20598
Main Entry	:	Vincent A. Cassella
Title Proper	:	A Clustering and Principal Component Approach to Exemplar Based Machine Learning for Classification Identification
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	Classifying detections is an important field of study in many disciplines. Typically,data can be represented in the form of a multidimensional vector defined within somehyperspace (e.g. One may have the sepal length, sepal width, petal length and petal widthof an iris flower.) One can view many classification problems as processing an unknowndata vector in some way thatClassifying detections is an important field of study in many disciplines. Typically,data can be represented in the form of a multidimensional vector defined within somehyperspace (e.g. One may have the sepal length, sepal width, petal length and petal widthof an iris flower.) One can view many classification problems as processing an unknowndata vector in some way that.
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL43738.pdf
Title and statement of responsibility and	:	A Clustering and Principal Component Approach to Exemplar Based Machine Learning for Classification Identification [Thesis]