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Executive Roundtable

Publisher:
IEEE
Year
: 2014
DOI: 10.1109/InfoSEEE.2014.6948071
URI: https://libsearch.um.ac.ir:443/fum/handle/fum/1037814
Keyword(s): data reduction,feedforward neural nets,learning (artificial intelligence),pattern classification,vectors,UCI machine learning repository,data classification,feedforward neural network,four-class synthetic problem,input vectors,minimum boundary vector distance selection,paired vector,reduced training set,training set reduction algorithm,Accuracy,Biological neural networks,Equations,Shape,Support vector machines,Training,Vectors,boundary detection,data reduction,neural netwo
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    Executive Roundtable

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date accessioned2020-03-12T21:07:30Z
date available2020-03-12T21:07:30Z
date issued2014
identifier other6925708.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1037814
formatgeneral
languageEnglish
publisherIEEE
titleExecutive Roundtable
typeConference Paper
contenttypeMetadata Only
identifier padid8164221
subject keywordsdata reduction
subject keywordsfeedforward neural nets
subject keywordslearning (artificial intelligence)
subject keywordspattern classification
subject keywordsvectors
subject keywordsUCI machine learning repository
subject keywordsdata classification
subject keywordsfeedforward neural network
subject keywordsfour-class synthetic problem
subject keywordsinput vectors
subject keywordsminimum boundary vector distance selection
subject keywordspaired vector
subject keywordsreduced training set
subject keywordstraining set reduction algorithm
subject keywordsAccuracy
subject keywordsBiological neural networks
subject keywordsEquations
subject keywordsShape
subject keywordsSupport vector machines
subject keywordsTraining
subject keywordsVectors
subject keywordsboundary detection
subject keywordsdata reduction
subject keywordsneural netwo
identifier doi10.1109/InfoSEEE.2014.6948071
journal titleigh-Performance Interconnects (HOTI), 2014 IEEE 22nd Annual Symposium on
filesize76674
citations0
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