Point Information Gain and Multidimensional Data Analysis

Dalibor \v{S}tys; Dmytro Soloviov; Jan Korbel; Jan Urban; Petr C\'isa\v{r}; Petr Mach\'a\v{c}ek; Renata Rycht\'arikov\'a

arxiv: 1501.02891 · v5 · pith:Y3E2FXX3new · submitted 2015-01-13 · ⚛️ physics.data-an

Point Information Gain and Multidimensional Data Analysis

Renata Rycht\'arikov\'a , Jan Korbel , Petr Mach\'a\v{c}ek , Petr C\'isa\v{r} , Jan Urban , Dmytro Soloviov , Dalibor \v{S}tys This is my paper

classification ⚛️ physics.data-an

keywords informationpointdataentropyanalysisgainmultidimensionalpied

0 comments

read the original abstract

We generalize the Point information gain (PIG) and derived quantities, i.e. Point information entropy (PIE) and Point information entropy density (PIED), for the case of R\'enyi entropy and simulate the behavior of PIG for typical distributions. We also use these methods for the analysis of multidimensional datasets. We demonstrate the main properties of PIE/PIED spectra for the real data on the example of several images, and discuss possible further utilization in other fields of data processing.

This paper has not been read by Pith yet.

Point Information Gain and Multidimensional Data Analysis

discussion (0)