In this paper, we first give an example to show that Theorem 1 in Hung and Yang (Inf Sci 178(6):1641–1650, 2008) does not hold, implying that the J-divergence introduced by Hung and Yang does not satisfy the axiomatic definition of intuitionistic fuzzy divergence measure. Inspired by th...
The representing measures can be determined in terms of the complex gamma function. We end by some simple considerations aiming at illuminating the signi- ficance of JSD-divergence. Consider the discrete case and introduce entropy as usual, i.e. H(P) = − n p n log p n (with p n...
In this section, we start from the Jensen-Shannon divergence and explore how this similarity measure can be used to construct a graph kernel method for two directed graphs. In particular, the kernel can be computed in terms of the entropies of two individual graphs and the entropy of their ...
2. Kernel PCA plots of two graph kernel methods on a number of undirected graphs generated from Erd˝os-R´enyi model and Barab´asi-Albert model. A Jensen-Shannon Divergence Kernel for Directed Graphs 205 3.3 Financial Data Analysis We turn our attention to the financial data, and ...
Our first idea is to design a new feature for the prediction of DNA-binding sites in proteins which leverages the Jensen–Shannon divergence 𝕁𝕊𝔻(𝐩𝑘∥𝐩𝑛𝑑):=ℍ((𝐩𝑘+𝐩𝑛𝑑)/2)−(ℍ(𝐩𝑘)+ℍ(𝐩𝑛𝑑))/2.𝕁𝕊𝔻pkpnd:=ℍpk+pnd/2−...
Our first idea is to design a new feature for the prediction of DNA-binding sites in proteins which leverages the Jensen–Shannon divergence 𝕁𝕊𝔻(𝐩𝑘∥𝐩𝑛𝑑):=ℍ((𝐩𝑘+𝐩𝑛𝑑)/2)−(ℍ(𝐩𝑘)+ℍ(𝐩𝑛𝑑))/2.𝕁𝕊𝔻pkpnd:=ℍpk+pnd/2−...