An EDA (Exploratory Data Analysis) framework based on K-FCA has been developed as an aid for scientific discovery. A more ad hoc tool, specifically designed for Gene Expression Analysis is also available in (url_WebGeneKFCA4GPM). https://webgenekfca.com/webgenekfca/general/changetype/webkfca
The Entropy Triangle
New implementations of the set of information-theoretic tools for the assessment of multi-class classifiers that include The Entropy Triangle, NIT and EMA.
- R Package and an initialisation file to configure the libraries dependencies.
- Weka package
- Matlab package
- Python package: to be released soon.
Use case vignettes in R
If you really want to get dirty, these are the use cases we will use to illustrate the affordances of the Entropy Triangle in Rmd: Analysis of Confusion Matrices and Simple Use Case for the CBET on classification. You will be able to analyse different classifiers and find out yourself what the Entropy Triangle is doing. In this case, it is recommended to have R Studio installed.
Our project in ResearchGate
Web page at ResearchGate where updates to it are posted:
The main papers for the theory
[bibshow file=http://www.tsc.uc3m.es/~carmen/CMET.bib] The first introduction to the Entropy Triangle CBET [bibcite key=val:pel:10b] and related metrics EMA \& NIT [bibcite key=val:pel:14a], the source multivariate extension SMET [bibcite key=val:pel:17b] and the channel multivariate extension CMET [bibcite key=val:pel:18c].
Our tutorial at WCCI18
Slides for IJCNN-04 tutorial: IJCNN18-EntropyTriangle
See more here.