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Document Type : Latin Dissertation
Language of Document : English
Record Number : 151586
Doc. No : ET23378
Main Entry : David R. Musicant
Title Proper : DATA MINING VIA MATHEMATICAL PROGRAMMING AND MACHINE LEARNING
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : This work e-xplores solving large-scale data mining problems through the use of mathe-mat ical programming met hods. In particular, algorithms are proposed for the supportvector machine (SVM) classification problem, which consists of constructing a separatings d a c e that can discriminate between points from one of two classes. An algorithm basedon successive overrelaxa t ion (SO R) is presented which can process very large dat asetsthat need not reside in memory. Concepts from generalized SVMs are combined withSOR and with linear programming to find nodinear separating surfaces. An "activeset" strategy is used to generate a fast algorithm that consists of solving a finite num-ber of linear equations of the order of the dimensionality of the original input space ateach step. This ASVM active set algorithm requires no specialized quadratic or linearprogramming code, but merely a linear equation solver which is publicly available. Animplicit Lagrangian for the dual of an SVM is used to lead to the simple linearly conver-.....-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL46617.pdf
Title and statement of responsibility and : DATA MINING VIA MATHEMATICAL PROGRAMMING AND MACHINE LEARNING [Thesis]
 
 
 
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