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Document Type : Latin Dissertation
Language of Document : English
Record Number : 149292
Doc. No : ET21084
Main Entry : Darrin P. Lewis
Title Proper : Combining Kernels for Classification
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Drawing inferences from large, heterogeneous data sets requires a theoretical frame-work that is capable of representing, for example, DNA and protein sequences, pro-tein structures, microarray expression data, various types of interaction networks, etc.Recently, a class of algorithms known as kernel methods has emerged as a powerfulframework for combining diverse types of data.The power and current popularity of kernel methods stem in part from theirability to handle diverse forms of structured inputs, including vectors, graphs, andstrings. The support vector machine (SVM) algorithm is the most popular kernelmethod, due to its theoretical.
Subject : Electericl tess
: برق
electronic file name : TL44232.pdf
Title and statement of responsibility and : Combining Kernels for Classification [Thesis]
 
 
 
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