Optimizing clustering-based analytical methods with trimmed and sparse clustering-Reference-Cited by-同舟云学术

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Optimizing clustering-based analytical methods with trimmed and sparse clustering

Published:2025-08 Issue: Volume:194 Page:110436
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Bernabé-Díaz José Antonio^ORCID,Franco Manuel^ORCID,Vivo Juana-María^ORCID,Fernández-Breis Jesualdo Tomás^ORCID

Funder

State Agency of Research

Publisher

Elsevier BV

Reference37 articles.

1. Cluster analysis of microarray data;Franco,2019

2. Evaluating the performances of biomarkers over a restricted domain of high sensitivity;Franco;Mathematics,2021

3. Rethinking an ROC partial area index for evaluating the classification performance at a high specificity range;Vivo;Adv. Data Anal. Classif.,2018

4. An automated process for supporting decisions in clustering-based data analysis;Bernabé-Díaz;Comput. Methods Programs Biomed.,2022

5. Algorithms for Clustering Data;Jain,1988

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