CLASSIFICATION METHODS FOR HIGH-DIMENSIONAL SPARSE DATA

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" CLASSIFICATION METHODS FOR HIGH-DIMENSIONAL SPARSE DATA "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	152233
Doc. No	:	ET24025
Main Entry	:	Tao Xiong
Title Proper	:	CLASSIFICATION METHODS FOR HIGH-DIMENSIONAL SPARSE DATA
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	Estimation of predictive classification models from high-dimensional, low sample size(HDLSS) data is becoming increasingly important in various applications such as genemicroarray analysis, image based object recognition, functional magnetic resonanceimaging (fMRI) analysis etc. For these applications, the dimensionality of the data vectoris much larger than the sample size. Such sparse data sets present new challenges forclassification learning methods..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL48179.pdf
Title and statement of responsibility and	:	CLASSIFICATION METHODS FOR HIGH-DIMENSIONAL SPARSE DATA [Thesis]