Analysis of Proposed and Traditional Boosting Algorithm with Standalone Classification Methods for Classifying Gene Expresssion Microarray Data Using a Reject Option

Adil Aslam Mira Department of Computer Science and Information Technology, King Abdullah Campus Chatter Kalas, University of Azad Jammu and Kashmir, Muzaffarabad, Azad Kashmir, PakistanView further author information

Lal Hussaina Department of Computer Science and Information Technology, King Abdullah Campus Chatter Kalas, University of Azad Jammu and Kashmir, Muzaffarabad, Azad Kashmir, Pakistan;b Department of Computer Science and Information Technology, Neelum Campus, University of Azad Jammu and Kashmir, Athmuqam, Azad Kashmir, PakistanCorrespondence[email protected]
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Muhammad Hammad Waseemb Department of Computer Science and Information Technology, Neelum Campus, University of Azad Jammu and Kashmir, Athmuqam, Azad Kashmir, PakistanView further author information

Amjad Aldweeshc College of Computer science and information technology, Shaqra University, Sahqra, Saudi ArabiaView further author information

Saim Rasheedd Department of Information Technology, Faculty of Computing and IT, King Abdulaziz University, Jeddah, Saudi ArabiaView further author information

El Sayed Yousefe Research Center for Advanced Materials Science (RCAMS), King Khalid University, Abha, Saudi Arabia;f Physics Dep. Faculty of Science, King Khalid University, Abha, Saudi ArabiaView further author information

Malik Sajjad Ahmed Nadeema Department of Computer Science and Information Technology, King Abdullah Campus Chatter Kalas, University of Azad Jammu and Kashmir, Muzaffarabad, Azad Kashmir, PakistanView further author information

Elsayed Tag Elding Faculty of Engineering and Technology, Future University in Egypt New Cairo, New Cairo, EgyptView further author information

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Analysis of Proposed and Traditional Boosting Algorithm with Standalone Classification Methods for Classifying Gene Expresssion Microarray Data Using a Reject Option

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Analysis of Proposed and Traditional Boosting Algorithm with Standalone Classification Methods for Classifying Gene Expresssion Microarray Data Using a Reject Option

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