online read us now
Paper details
Number 3 - September 2021
Volume 31 - 2021
Fitting a Gaussian mixture model through the Gini index
Adriana Laura López-Lobato, Martha Lorena Avendaño-Garrido
Abstract
A linear combination of Gaussian components is known as a Gaussian mixture model. It is widely used in data mining
and pattern recognition. In this paper, we propose a method to estimate the parameters of the density function given by
a Gaussian mixture model. Our proposal is based on the Gini index, a methodology to measure the inequality degree
between two probability distributions, and consists in minimizing the Gini index between an empirical distribution for the
data and a Gaussian mixture model. We will show several simulated examples and real data examples, observing some of
the properties of the proposed method.
Keywords
Gini index problem, Gaussian mixture model, clustering.