Probabilistic entropy measures derived by using conic-section equation and their application in dimension reduction. Issue 6 (18th August 2019)

• Record Type: Journal Article
• Authors: Sharma, Omdutt; Gupta, Priti
• Is Part Of: Journal of statistics & management systems. Volume 22:Issue 6(2019)
• Page Start: 1163
• Page End: 1181
• Publication Date: 2019-08-18
• Subjects: 94A15 -- 62B10; Entropy -- Probabilistic entropy -- Conic section -- Circle -- Ellipse -- Parabola -- Hyperbola; Statistics -- Periodicals; Mathematical models -- Periodicals; Mathematical models; Statistics; Periodicals; 519.5
• DOI: 10.1080/09720510.2019.1596593
• Languages: English
• ISSNs: 0972-0510

Abstract

Abstract: Entropy is a significant measure of information theory used as to measure the uncertainty or quantities the information's contained in data or information in any experiment or process. Thus keeping in the view of the importance of entropy here some probabilistic entropy measures have been derived by using the equations' of conic-sections with their validity. The application of proposed entropy measures in feature selection and decision making problem is also discussed.