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

von Thuy T. Pham

107 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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.

• Reihe: Springer Theses
• ISBN: 9783030075187
• Sprache: Englisch
• Erscheinungsdatum: 25.01.2019
• Genre: Technik/Sonstiges
• Verlag: Springer International Publishing