Classification of Generalized Weighted Cross-entropic Models for Discrete Probability Distribution in Vague Setting
Rohit Kumar Verma *
Department of Mathematics, Bharti Vishwavidyalaya, Durg, Chhattisgarh, India.
*Author to whom correspondence should be addressed.
Abstract
The ambiguity of a novel class of generalized weighted cross-entropy models based on discrete probability distributions is the main topic of this paper. A well-known constrained symmetrization of the Kullback-Leibler cross-entropy, the Jensen-Shannon divergence does not require matching support for probability densities. This paper is novel in that it derives a vector-skew Jensen-Shannon divergence by obtaining different cross-entropies for different values of a prevalent scalar A, determining the concavity of the measure with respect to that scalar, and introducing a vector-skew generalization of it.
Keywords: Weighted cross-entropy, discrete probability distribution, vagueness, shannon entropy