Michał Szkibiel

Evaluating machine learning algorithms: The role of sample size and quality

SVM was the most consistent and reliable method across the tested scenarios, achieving high classification accuracy over a wide range of training sample sizes and maintaining strong robustness under noisy labels, which makes it a strong baseline choice when reference data are limited or imperfect.