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.
| ISBN: | 9783030075187 |
| Publication date: | 25th January 2019 |
| Author: | Thuy T Pham |
| Publisher: | Springer Nature Switzerland AG |
| Format: | Paperback |
| Pagination: | 107 pages |
| Series: | Springer Theses |
| Genres: |
Biomedical engineering Data mining Expert systems / knowledge-based systems Artificial intelligence Computational biology / bioinformatics |
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.
Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings features in the following genres: Biomedical engineering, Data mining, Expert systems / knowledge-based systems, Artificial intelligence, Computational biology / bioinformatics
Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings is available in Paperback, Hardback
Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings was written by Thuy T Pham and published by Springer Nature Switzerland AG
Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings has 107 pages
Yes it is part of Springer Theses series
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