Applying Machine Learning For Automated Classification Of Biomedical Data In Subjectindependent Settings 1st Ed Thuy T Pham by Thuy T. Pham 9783319986746, 9783319986753, 3319986740, 3319986759 instant download after payment.

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.