The Expectation Maximisation (EM) algorithm is a procedure that iteratively optimises parameters of a given model, to maximise the likelihood of observing a given (training) dataset. Assuming that our framework has unobserved data, X, observed data, Y , parameters Θ, and a likelihood function L(X,Y,Θ) = P(X,Y |Θ), we can derive the steps of the algorithm as follows: 1. Choose initial parameters...

Let μ and λ be two positive bounded measures on the same meaurable space (Ω,F). We call μ and λ equivalent, and write μ ≡ λ, if they have the same null sets— so, if they were probability measures, the notion of “a.s.” would be the same for both. More generally, we call λ absolutely continuous (AC) w.r.t. μ, and write λ μ, if μ(A) = 0 implies λ(A) = 0, i.e., if every μ-null set is also λ-null. W...

Abstract The objective of this article is to define the financial inclusion expectation gap, offer some insight into nature and causes it, suggest ways reduce gap. discussion in provides helpful insights problem towards achieving United Nations Sustainable Development Goals. It hoped that such an attempt can provide understand gap inclusion.