On Coarse Graining of Information and Its Application to Pattern Recognition

12 Nov 2014 • Ali Ghaderi

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... (read more)

PDF Abstract

Code

Add Remove Mark official

No code implementations yet. Submit your code now

Tasks

Add Remove

Results from the Paper

Add Remove

Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

METHOD	TYPE
🤖 No Methods Found	Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet

On Coarse Graining of Information and Its Application to Pattern Recognition

Code

Add Remove Mark official

Tasks

Add Remove

Datasets

Results from the Paper

Add Remove

Methods used in the Paper

Add Remove

Edit Social Preview

On Coarse Graining of Information and Its Application to Pattern Recognition Edit social preview

Code Edit Add Remove Mark official

Tasks Edit Add Remove

Datasets Edit

Results from the Paper Edit Add Remove

Methods used in the Paper Edit Add Remove

On Coarse Graining of Information and Its Application to Pattern Recognition

Code

Add Remove Mark official

Tasks

Add Remove

Datasets

Results from the Paper

Add Remove

Methods used in the Paper

Add Remove