Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings
Author: Thuy T. Pham
Publisher: Springer
Published: 2018-08-23
Total Pages: 114
ISBN-13: 3319986759
DOWNLOAD EBOOKThis 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.