Effective Feature Selection Method for Class-Imbalance Datasets Applied to Chemical Toxicity Prediction
Author:
Affiliation:
1. Cheminformatic Group, University of Informatics Science, 19370Havana, Cuba
2. Department of Computing and Numerical Analysis, University of Córdoba, Campus de Rabanales, Albert Einstein Building, E-14071 Córdoba, Spain
Funder
Junta de Andaluc?a
Ministerio de Ciencia e Innovaci?n
European Regional Development Fund
Universidad de C?rdoba
Publisher
American Chemical Society (ACS)
Subject
Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.0c00908
Reference49 articles.
1. FeatureSelect: a software for feature selection based on machine learning approaches
2. Oversampling to Overcome Overfitting: Exploring the Relationship between Data Set Composition, Molecular Descriptors, and Predictive Modeling Methods
3. A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
4. Ensembles of feature selectors for dealing with class-imbalanced datasets: A proposal and comparative study
5. Drug-target interaction prediction via class imbalance-aware ensemble learning
Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Chemical space deconstruction-based dynamic model ensemble architecture for molecular property prediction;Chemical Engineering Science;2024-08
2. Optimized Ensembled Predictive Model for Drug Toxicity;Communications in Computer and Information Science;2023-12-03
3. Descriptive Analysis of Feature Selection and Clustering Algorithms for Optimized Drug Toxicity Prediction Model;2023 6th International Conference on Contemporary Computing and Informatics (IC3I);2023-09-14
4. Performance Analysis of Drug Toxicity Prediction Using Machine Learning Approaches;2023 3rd International Conference on Innovative Sustainable Computational Technologies (CISCT);2023-09-08
5. RUE: A robust personalized cost assignment strategy for class imbalance cost-sensitive learning;Journal of King Saud University - Computer and Information Sciences;2023-04
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3