Cargando…
Mimicking Complexity of Structured Data Matrix’s Information Content: Categorical Exploratory Data Analysis
We develop Categorical Exploratory Data Analysis (CEDA) with mimicking to explore and exhibit the complexity of information content that is contained within any data matrix: categorical, discrete, or continuous. Such complexity is shown through visible and explainable serial multiscale structural de...
Autores principales: | Hsieh, Fushing, Chou, Elizabeth P., Chen, Ting-Li |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151017/ https://www.ncbi.nlm.nih.gov/pubmed/34064857 http://dx.doi.org/10.3390/e23050594 |
Ejemplares similares
-
Categorical Exploratory Data Analysis: From Multiclass Classification and Response Manifold Analytics Perspectives of Baseball Pitching Dynamics
por: Hsieh, Fushing, et al.
Publicado: (2021) -
Categorical Nature of Major Factor Selection via Information Theoretic Measurements
por: Chen, Ting-Li, et al.
Publicado: (2021) -
From patterned response dependency to structured covariate
dependency: Entropy based categorical-pattern-matching
por: Fushing, Hsieh, et al.
Publicado: (2018) -
Complex surveys: analysis of categorical data
por: Mukhopadhyay, Parimal
Publicado: (2016) -
Learned Practical Guidelines for Evaluating Conditional Entropy and Mutual Information in Discovering Major Factors of Response-vs.-Covariate Dynamics
por: Chen, Ting-Li, et al.
Publicado: (2022)