Web application for research of the influence of hyperparameters on the performance of machine learning algorithms in early diagnosis of diseases

E. V. Timoschenko ; A. F. Razhkov

Problemy fiziki, matematiki i tehniki, no. 1 (2025), pp. 113-119

Résumé

The article presents a software implementation of a web application for studying the influence of hyperparameters on the effectiveness of machine learning algorithms when solving problems of classification of biomedical data and predicting the presence of diseases as a continuation of previous studies on optimizing hyperparameters of machine learning algorithms for problems of classification of biomedical data. The web application is designed to facilitate the process of setting up models, providing a convenient tool for conducting experiments, making it possible to load a set of biomedical data, select a classification algorithm and set values for the corresponding hyperparameters. It can also be used as a medical decision support tool, providing more accurate diagnosis based on the analysis of the patient clinical data.

Détail

Keywords: hyperparameters, machine learning model, classification algorithms, performance assessment, early diagnosis of diseases, predictive analytics, web application.