Name
Abstract | ||
|---|---|---|
We extend a framework for the analysis of classifiers to encompass also the analysis of data sets. Specifically, we generalize a balance equation and a visualization device, the Entropy Triangle, for multivariate distributions, not only bivariate ones. With such tools we analyze a handful of UCI machine learning task to start addressing the question of how information gets transformed through machine learning classification tasks. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-32034-2_54 | HYBRID ARTIFICIAL INTELLIGENT SYSTEMS |
Field | DocType | Volume |
Data mining,Data analysis,Computer science,Multivariate normal distribution,Artificial intelligence,Bivariate analysis,Pattern recognition,Multivariate statistics,Visualization,Balance equation,Mutual information,Statistical classification,Machine learning | Conference | 9648 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.37 |
References | Authors | |
6 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francisco J. Valverde-Albacete | 1 | 116 | 20.84 |
| Carmen Peláez-moreno | 2 | 130 | 22.07 |