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Thesis

Methods of classification of the cardiotocogram

Abstract:

This Thesis compares CTG classification techniques proposed in the literature and their potential extensions. A comparison between four classifiers previously assessed - Adaboost, Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Machine (SVM) - and two proposed classifiers - Bayesian ANN (BANN), Relevance Vector Machine - was conducted using a database of 7,568 cases and two open source databases. The Random Forest (RF) achieved the highest average result and was propos...

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Division:
MPLS
Department:
Engineering Science
Department:
University of Oxford
Role:
Author

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Department:
University of Oxford
Role:
Supervisor
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
Language:
English
Keywords:
Subjects:
UUID:
uuid:550bb5ea-bee8-4eb8-95e2-f16c54d7cd68
Deposit date:
2017-04-27

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