A Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine

After the emergence of Artificial Intelligence (AI), great developments have taken place in the fields of science, economics, medicine and all other fields that use computer science. Along with the resulting developments in these fields, artificial intelligence has also solved many intractable probl...

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Autores principales:	Yassin Benajiba, Mohamed Chrayah, Yassine Al-Amrani
Formato:	article
Lenguaje:	EN FR
Publicado:	EDP Sciences 2021
Materias:	ai svm kernel function Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/9e36ff0cbbca418a84e60ba99ca32d15
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id	oai:doaj.org-article:9e36ff0cbbca418a84e60ba99ca32d15
record_format	dspace
spelling	oai:doaj.org-article:9e36ff0cbbca418a84e60ba99ca32d152021-11-12T11:44:08ZA Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine2267-124210.1051/e3sconf/202131901103https://doaj.org/article/9e36ff0cbbca418a84e60ba99ca32d152021-01-01T00:00:00Zhttps://www.e3s-conferences.org/articles/e3sconf/pdf/2021/95/e3sconf_vigisan_01103.pdfhttps://doaj.org/toc/2267-1242After the emergence of Artificial Intelligence (AI), great developments have taken place in the fields of science, economics, medicine and all other fields that use computer science. Along with the resulting developments in these fields, artificial intelligence has also solved many intractable problems, such as predicting specific serious diseases, determining future product sales, as well as analyzing and studying big data in the shortest possible time … SVM is one of the most important technologies in this field of artificial intelligence that goes into supervised methods, and which every machine learning expert should have in his/her arena. For this reason, in this article, we studied this technique and determined its advantages and disadvantages as well as its fields of application. Next, we applied this technique to three different databases, using four basis change functions, and we compared the results obtained to determine the best way to use the basis change functions.Yassin BenajibaMohamed ChrayahYassine Al-AmraniEDP Sciencesarticleaisvmkernel functionEnvironmental sciencesGE1-350ENFRE3S Web of Conferences, Vol 319, p 01103 (2021)
institution	DOAJ
collection	DOAJ
language	EN FR
topic	ai svm kernel function Environmental sciences GE1-350
spellingShingle	ai svm kernel function Environmental sciences GE1-350 Yassin Benajiba Mohamed Chrayah Yassine Al-Amrani A Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine
description	After the emergence of Artificial Intelligence (AI), great developments have taken place in the fields of science, economics, medicine and all other fields that use computer science. Along with the resulting developments in these fields, artificial intelligence has also solved many intractable problems, such as predicting specific serious diseases, determining future product sales, as well as analyzing and studying big data in the shortest possible time … SVM is one of the most important technologies in this field of artificial intelligence that goes into supervised methods, and which every machine learning expert should have in his/her arena. For this reason, in this article, we studied this technique and determined its advantages and disadvantages as well as its fields of application. Next, we applied this technique to three different databases, using four basis change functions, and we compared the results obtained to determine the best way to use the basis change functions.
format	article
author	Yassin Benajiba Mohamed Chrayah Yassine Al-Amrani
author_facet	Yassin Benajiba Mohamed Chrayah Yassine Al-Amrani
author_sort	Yassin Benajiba
title	A Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine
title_short	A Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine
title_full	A Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine
title_fullStr	A Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine
title_full_unstemmed	A Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine
title_sort	nonlinear support vector machine analysis using kernel functions for nature and medicine
publisher	EDP Sciences
publishDate	2021
url	https://doaj.org/article/9e36ff0cbbca418a84e60ba99ca32d15
work_keys_str_mv	AT yassinbenajiba anonlinearsupportvectormachineanalysisusingkernelfunctionsfornatureandmedicine AT mohamedchrayah anonlinearsupportvectormachineanalysisusingkernelfunctionsfornatureandmedicine AT yassinealamrani anonlinearsupportvectormachineanalysisusingkernelfunctionsfornatureandmedicine AT yassinbenajiba nonlinearsupportvectormachineanalysisusingkernelfunctionsfornatureandmedicine AT mohamedchrayah nonlinearsupportvectormachineanalysisusingkernelfunctionsfornatureandmedicine AT yassinealamrani nonlinearsupportvectormachineanalysisusingkernelfunctionsfornatureandmedicine
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A Nonlinear Support Vector Machine Analysis Using Kernel Functions for Nature and Medicine

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