Development of an Online Model Evaluation and Comparison Platform
Data Science — 2025, Undergraduate
This study developed an online model evaluation and comparison platform that runs cross-validation, computes confusion matrices, and compares candidate models side by side. The platform recommends models by metric and stores experiments. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Node.js, Express, and MongoDB. The findings showed that the platform standardised evaluation and reduced comparison effort, while achieving a high System Usability Scale score. The study recommends use in model selection workflows.
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