Figure 6
From: Distribution Optimization: An evolutionary algorithm to separate Gaussian mixtures
Fit of a GMM with M = 3 modes to data set 4. (microarray derived gene expression data form patients with leukemia and controls15). The distribution of the data is shown as probability density function (PDF) estimated by means of the Pareto density estimation (PDE23; black line) and overlaid on a histogram. The GMM fit is shown as a red line and the M = 3 single mixes are indicated as differently colored dashed lines (M#1, …, M#3). The Bayesian boundaries between the Gaussians are indicated as perpendicular magenta lines. At the right of the distributions, the respective QQ-plots are shown. Top: Fit obtained with the automated “Distribution Optimization” algorithm. Bottom: Fit obtained using the EM algorithm without manual interaction. The figure has been created using the R software package (version 3.5.3 for Linux; http://CRAN.R-project.org/24) and the R libraries “AdaptGauss” (https://cran.r-project.org/package=AdaptGauss12) and “DistributionOptimization” (https://cran.r-project.org/package=DistributionOptimization).
