Pham T.T. Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings

Cham: Springer International Publishing, 2019. — 107 p. — ISBN: 978-3-319-98675-3.This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings