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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 10, ISSUE 1, JANUARY 2021

Supervised, Unsupervised and Semi-supervised learning

Sujata Gawade, Pournima Kamle

DOI: 10.17148/IJARCCE.2021.10137

Abstract: Feature selection is a big task and its challenge for high dimensional data. Semi-supervised feature selection is a combination of supervised and unsupervised data. Supervised data means labelled data and unsupervised data means unlabelled data. In semi-supervised feature selection unlabelled data is more than labelled data. Supervised learning means well labelled data that means data is already labelled with correct answer. Unsupervised data means that data is neither labelled nor classified and allowing algorithm to process without guidance. Supervised learning use processes like regression and classification. Algorithms used for unsupervised learning clustering and association. In supervised learning optimized performance criteria with the help of previous experience.

Keywords: Supervised, Semi-supervised, labelled, and unlabelled.

How to Cite:

[1] Sujata Gawade, Pournima Kamle, “Supervised, Unsupervised and Semi-supervised learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.10137