Some Studies of Expectation Maximization Clustering Algorithm to Enhance Performance

Expectation Maximization (EM) is an efficient mixture-model based clustering method. In this paper, authors made an attempt to scale-up the algorithm, by reducing the computation time required for computing quadratic term, without sacrificing the accuracy. Probability density function (pdf) is to be calculated in EM, which involves evaluating quadratic term calculation. Three recursive approaches are introduced for quadratic term computation. As per our observation, the standard EM needs O(d² ) computations for quadratic term computation, where d is number of dimensions. The proposed recursive EM approaches are with time complexity of O(d²/2) for the quadratic term computation.