INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Overview of Supervised Machine Learning Methods & Future Scope
Authors Name:
Prem Kumar
Unique Id:
IJSDR2006105
Published In:
Volume 5 Issue 6, June-2020
Abstract:
Supervised machine learning is the search for algorithms that reason from externally supplied instances to produce general hypotheses, which then make predictions about future instances. In other words, the goal of supervised learning is to build a concise model of the distribution of class labels in terms of predictor features. The resulting classifier is then used to assign class labels to the testing instances where the values of the predictor features are known, but the value of the class label is unknown. This paper describes various supervised machine learning classification techniques. Of course, a single article cannot be a complete review of all supervised machine learning classification algorithms (also known induction classification algorithms), yet we hope that the references cited will cover the major theoretical issues, guiding the researcher in interesting research directions and suggesting possible bias combinations that have yet to be explored.
"Overview of Supervised Machine Learning Methods & Future Scope", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 6, page no.622 - 629, June-2020, Available :http://www.ijsdr.org/papers/IJSDR2006105.pdf
Downloads:
000337212
Publication Details:
Published Paper ID: IJSDR2006105
Registration ID:192002
Published In: Volume 5 Issue 6, June-2020
DOI (Digital Object Identifier):
Page No: 622 - 629
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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