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Improving the performance of machine learning classifiers for Breast Cancer diagnosis based on feature selection

Author:
Perez, N.
,
Guevara, M.A.
,
Silva, A.
,
Ramos, I.
,
Loureiro, J.
Publisher:
IEEE
Year
: 2014
DOI: 10.1109/ICALIP.2014.7009927
URI: https://libsearch.um.ac.ir:443/fum/handle/fum/1043709
Keyword(s): Arrays,Direction-of-arrival estimation,Estimation,Frequency estimation,Joints,Signal processing algorithms,Vectors,array signal processing,direction of arrival,frequency of arrival
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    Improving the performance of machine learning classifiers for Breast Cancer diagnosis based on feature selection

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contributor authorPerez, N.
contributor authorGuevara, M.A.
contributor authorSilva, A.
contributor authorRamos, I.
contributor authorLoureiro, J.
date accessioned2020-03-12T21:17:30Z
date available2020-03-12T21:17:30Z
date issued2014
identifier other6933015.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1043709
formatgeneral
languageEnglish
publisherIEEE
titleImproving the performance of machine learning classifiers for Breast Cancer diagnosis based on feature selection
typeConference Paper
contenttypeMetadata Only
identifier padid8171817
subject keywordsArrays
subject keywordsDirection-of-arrival estimation
subject keywordsEstimation
subject keywordsFrequency estimation
subject keywordsJoints
subject keywordsSignal processing algorithms
subject keywordsVectors
subject keywordsarray signal processing
subject keywordsdirection of arrival
subject keywordsfrequency of arrival
identifier doi10.1109/ICALIP.2014.7009927
journal titleomputer Science and Information Systems (FedCSIS), 2014 Federated Conference on
filesize317879
citations0
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