Controlling Feature Selection in Random Forests of Decision Trees Using a Genetic Algorithm: Classification of Class I MHC Peptides-Reference-Cited by-同舟云学术

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Controlling Feature Selection in Random Forests of Decision Trees Using a Genetic Algorithm: Classification of Class I MHC Peptides

Published:2009-06-01 Issue:5 Volume:12 Page:514-519
ISSN:1386-2073
Container-title:Combinatorial Chemistry & High Throughput Screening
language:en
Short-container-title:CCHTS

Author:

Hansen Loren,Lee Ernestine,Hestir Kevin,Williams Lewis,Farrelly David

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

Cited by 11 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. An Evolutionary Approach to Feature Selection and Classification;Lecture Notes in Computer Science;2024

2. Feature Selection Based on a Decision Tree Genetic Algorithm;Lecture Notes in Computer Science;2023

3. MHC2AffyPred : A machine‐learning approach to estimate affinity of MHC class II peptides based on structural interaction fingerprints;Proteins: Structure, Function, and Bioinformatics;2022-10-03

4. MHCII3D—Robust Structure Based Prediction of MHC II Binding Peptides;International Journal of Molecular Sciences;2020-12-22

5. Classification of abdominal ECG recordings for the identification of fetal risk using random forest and optimal feature selection;14th International Symposium on Medical Information Processing and Analysis;2018-12-21

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