KITONDUA LUBANZADIO Richard

Optimization of Gradient Descent and Loss Function: Application to Prediction of Depression by Multidimensional Analysis of Key Factors

DJEMBA NSEYA Chantal, KAFUNDA KATALAY Pierre, KITONDUA LUBANZADIO Richard, KASIAMA NGI ONKOR Joseph, LUBONGO MUEMBE Georgine, OKITOLONDA NDJATE Emile & SHAKO KONDE Marie Francine · Asian Journal of Research in Computer Science · 2026

This study explores the application of gradient descent optimization and loss functions for depression prediction through multidimensional analysis of behavioral, psychological, and social factors. A logistic regression model was trained on a set of 1,631 records. Experimental re...

Open access Research Article 10.9734/ajrcos/2026/v19i1803

Construction of a Random Forest-based Machine Learning Model for Depression Prediction: Application to the Analysis of Disordered Behaviors

DJEMBA NSEYA Chantal, KAFUNDA KATALAY Pierre, KITONDUA LUBANZADIO Richard, ESENGANDJI OKAKO Elizabeth, TSHIBAMBA BUATSHIA Betch, SHAKO KONDE Marie Francine, MUKUNA WA MUKUNA Fader & MANDE KUMWIMBA Hydrice · Asian Journal of Research in Computer Science · 2025

The topics covered in this article include the creation of a bootstrap learning model for depression predictions based on the Random Forest technique. Depression is a severe mental illness that affects millions of people worldwide. This condition causes great pain and affects qua...

Open access Research Article 10.9734/ajrcos/2025/v18i9751