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Remote lab experiments for take away

contributor authorZimmer, T.
contributor authorBillaud, M.
contributor authorPic, M.
contributor authorGeoffroy, D.
date accessioned2020-03-12T22:27:57Z
date available2020-03-12T22:27:57Z
date issued2014
identifier other7011097.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/1083958?locale-attribute=en&show=full
formatgeneral
languageEnglish
publisherIEEE
titleRemote lab experiments for take away
typeConference Paper
contenttypeMetadata Only
identifier padid8221188
subject keywordsBayes methods
subject keywordsn data mining
subject keywordsn directed graphs
subject keywordsn learning (artificial intelligence)
subject keywordsn pattern classification
subject keywordsn DWNB
subject keywordsn NB classification
subject keywordsn attribute weighted model
subject keywordsn data mining
subject keywordsn dual weighted model
subject keywordsn embedded instance weights
subject keywordsn instance similarity based method
subject keywordsn machine learning
subject keywordsn naive Bayes classification
subject keywordsn probability value
subject keywordsn training data
subject keywordsn training instance
subject keywordsn Accuracy
subject keywordsn Bayes methods
subject keywordsn Data mining
subject keywordsn Niobium
subject keywordsn Training
subject keywordsn Train
identifier doi10.1109/IJCNN.2014.6889572
journal titlenteractive Mobile Communication Technologies and Learning (IMCL), 2014 International Conference on
filesize748587
citations1


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