CLASSify: A Web-Based Tool for Machine Learning
This tool addresses the accessibility gap for bioinformatics researchers who lack machine learning expertise, though it is incremental as it builds on existing methods.
The authors tackled the problem of technical barriers in machine learning classification for bioinformatics researchers by developing CLASSify, an automated web-based tool that simplifies model training, optimization, and inference, providing visualizations, synthetic data generation, and explainability scores.
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.