Cargando…
Modified Mahalanobis Taguchi System for Imbalance Data Classification
The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated...
Autor principal: | El-Banna, Mahmoud |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5546084/ https://www.ncbi.nlm.nih.gov/pubmed/28811820 http://dx.doi.org/10.1155/2017/5874896 |
Ejemplares similares
-
The Mahalanobis-Taguchi system /
por: Taguchi, Genichi, 1924-
Publicado: (2001) -
Optimized Mahalanobis–Taguchi System for High-Dimensional Small Sample Data Classification
por: Xiao, Xinping, et al.
Publicado: (2020) -
Intelligent Fault Diagnosis of Industrial Robot Based on Multiclass Mahalanobis-Taguchi System for Imbalanced Data
por: Sun, Yue, et al.
Publicado: (2022) -
Adaptive Multiclass Mahalanobis Taguchi System for Bearing Fault Diagnosis under Variable Conditions
por: Wang, Ning, et al.
Publicado: (2018) -
Development of a Screening Method for Health Hazard Ranking and Scoring of Chemicals Using the Mahalanobis–Taguchi System
por: Huh, Da-An, et al.
Publicado: (2018)