Machine Learning, Clustering, Gaussian Mixture Model.
Computational Statistics in Python, Duke University The E step starts with a fixed θ(t), and attempts to maximize the lower bound(LB) function F(q(z), θ) with respect to q(z). Intuitively, this happens when the LB function meets the objective likelihood function. Mathematically, this is the case