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

Springer Theses

By (author) Thuy T. Pham
Format: Hardback
Publisher: Springer International Publishing AG, Cham, Switzerland
Published: 31st Aug 2018
Dimensions: w 156mm h 234mm d 8mm
Weight: 355g
ISBN-10: 3319986740
ISBN-13: 9783319986746
Barcode No: 9783319986746
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Synopsis
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.

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