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The Institute has a unique distinction of publishing a bi-annual International journal DIAS Technology Review – The International Journal for Business and IT. The Editorial Board comprises of...

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Vol. 21 No. 1 (2024)

Articles 41th Edition of DTR Apr 2024 – Mar 2024

Hybrid Information Theoretic Measures and Their Applications inData Mining

Authors
DR
Dr. Sonia

Assistant Professor cum Statistician, NC Medical College, Israna, Panipat, India
20 Views
11 Downloads
Published 2024-09-30
Pages 96-110
Abstract

Information theory, introduced by Shannon (1948), revolutionized the understanding of communication and uncertainty by providing a mathematical measure of information through entropy. Shannon entropy quantifies the average uncertainty associated with a random variable
and has been widely applied in communication systems, statistics, pattern recognition, machine learning, and signal processing. Despite its
success, Shannon’s framework relies on precise probability distributions, which are often unavailable or unreliable in practical situations.

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How to Cite
Dr. Sonia . (2024). Hybrid Information Theoretic Measures and Their Applications inData Mining. DIAS Technology Review, 21(1), 96-110.
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