The cluster correlation-network support vector machine for high-dimensional binary classification

DOI10.1080/00949655.2019.1575382OpenAlexW2911876654WikidataQ128393789 ScholiaQ128393789MaRDI QIDQ5107375

Karim Oualkacha, Abdallah Mkhadri, Rachid Kharoubi

Publication date: 27 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2019.1575382

zbMATH Keywords

classificationclusteringshrinkagesupport vector machinevariables selection

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items (1)

A survey of statistical learning techniques as applied to inexpensive pediatric obstructive sleep apnea data

Uses Software

• WGCNA
• ElemStatLearn
• AS 136
• gglasso
• NbClust
• FATCAT

Cites Work

• Unnamed Item
• Estimating the Number of Clusters in a Data Set Via the Gap Statistic
• Algorithm AS 136: A K-Means Clustering Algorithm
• Nearly unbiased variable selection under minimax concave penalty
• A smoothed EM-algorithm for DNA methylation profiles from sequencing-based methods in cell lines or for a single cell type
• A coordinate descent algorithm for computing penalized smooth quantile regression
• Support-vector networks
• The statistical theory of shape
• An Introduction to Statistical Learning
• A General Framework for Weighted Gene Co-Expression Network Analysis
• A fast unified algorithm for solving group-lasso penalize learning problems

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