Cargando…
Assessing Information Transmission in Data Transformations with the Channel Multivariate Entropy Triangle
Data transformation, e.g., feature transformation and selection, is an integral part of any machine learning procedure. In this paper, we introduce an information-theoretic model and tools to assess the quality of data transformations in machine learning tasks. In an unsupervised fashion, we analyze...
Autores principales: | Valverde-Albacete, Francisco J., Peláez-Moreno, Carmen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7844629/ https://www.ncbi.nlm.nih.gov/pubmed/33265588 http://dx.doi.org/10.3390/e20070498 |
Ejemplares similares
-
The Case for Shifting the Rényi Entropy
por: Valverde-Albacete, Francisco J., et al.
Publicado: (2019) -
The Rényi Entropies Operate in Positive Semifields
por: Valverde-Albacete, Francisco J., et al.
Publicado: (2019) -
100% Classification Accuracy Considered Harmful: The Normalized Information Transfer Factor Explains the Accuracy Paradox
por: Valverde-Albacete, Francisco J., et al.
Publicado: (2014) -
Interactive knowledge discovery and data mining on genomic expression data with numeric formal concept analysis
por: González-Calabozo, Jose M, et al.
Publicado: (2016) -
Entropy transmission for quantum channels
por: Mukhamedov, F
Publicado: (2002)