Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings
Produktnummer:
18af12ab65c8194778a77f640c4c69da30
| Autor: | Pham, Thuy T. |
|---|---|
| Themengebiete: | Anomaly Detection for Biomedical Data Anomaly Score Based Detector Automated Feature Selection Feature Selection Based on Voting Learning for Detecting Freezing of Gait Events Novelty Detection Unsupervised Anomaly Detection Unsupervised Artifact Detection Unsupervised Multi-class Sorting Voting Process for Feature Selection |
| Veröffentlichungsdatum: | 25.01.2019 |
| EAN: | 9783030075187 |
| Sprache: | Englisch |
| Seitenzahl: | 107 |
| Produktart: | Kartoniert / Broschiert |
| Verlag: | Springer International Publishing |
Produktinformationen "Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings"
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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