On Coarse Graining of Information and Its Application to Pattern Recognition
Computer Vision and Pattern Recognition
2015-06-23 v1 Machine Learning
Abstract
We propose a method based on finite mixture models for classifying a set of observations into number of different categories. In order to demonstrate the method, we show how the component densities for the mixture model can be derived by using the maximum entropy method in conjunction with conservation of Pythagorean means. Several examples of distributions belonging to the Pythagorean family are derived. A discussion on estimation of model parameters and the number of categories is also given.
Keywords
Cite
@article{arxiv.1411.3169,
title = {On Coarse Graining of Information and Its Application to Pattern Recognition},
author = {Ali Ghaderi},
journal= {arXiv preprint arXiv:1411.3169},
year = {2015}
}