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CLASSify: A Web-Based Tool for Machine Learning.

Authors :
Mullen AD
Armstrong SE
Talbert J
Bumgardner VKC
Source :
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science [AMIA Jt Summits Transl Sci Proc] 2024 May 31; Vol. 2024, pp. 364-373. Date of Electronic Publication: 2024 May 31 (Print Publication: 2024).
Publication Year :
2024

Abstract

Machine learning classification problems are widespread in bioinformatics, but the technical knowledge required to perform model training, optimization, and inference can prevent researchers from utilizing this technology. This article presents an automated tool for machine learning classification problems to simplify the process of training models and producing results while providing informative visualizations and insights into the data. This tool supports both binary and multiclass classification problems, and it provides access to a variety of models and methods. Synthetic data can be generated within the interface to fill missing values, balance class labels, or generate entirely new datasets. It also provides support for feature evaluation and generates explainability scores to indicate which features influence the output the most. We present CLASSify, an open-source tool for simplifying the user experience of solving classification problems without the need for knowledge of machine learning.<br /> (©2024 AMIA - All rights reserved.)

Details

Language :
English
ISSN :
2153-4063
Volume :
2024
Database :
MEDLINE
Journal :
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Publication Type :
Academic Journal
Accession number :
38827105