Cargando…
Information Theory-Based Feature Selection: Minimum Distribution Similarity with Removed Redundancy
Feature selection is an important preprocessing step in pattern recognition. In this paper, we presented a new feature selection approach in two-class classification problems based on information theory, named minimum Distribution Similarity with Removed Redundancy (mDSRR). Different from the previo...
Autores principales: | Zhang, Yu, Lin, Zhuoyi, Kwoh, Chee Keong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302551/ http://dx.doi.org/10.1007/978-3-030-50426-7_1 |
Ejemplares similares
-
Class similarity network for coding and long non-coding RNA classification
por: Zhang, Yu, et al.
Publicado: (2021) -
Kernel Partial Least Squares Feature Selection Based on Maximum Weight Minimum Redundancy
por: Liu, Xiling, et al.
Publicado: (2023) -
Minimum redundancy maximum relevance feature selection approach for temporal gene expression data
por: Radovic, Milos, et al.
Publicado: (2017) -
AlPOs Synthetic Factor Analysis Based on Maximum Weight and Minimum Redundancy Feature Selection
por: Guo, Yuting, et al.
Publicado: (2013) -
PREAL: prediction of allergenic protein by maximum Relevance Minimum Redundancy (mRMR) feature selection
por: Wang, Jing, et al.
Publicado: (2013)