The University of Southampton

Classification of Imbalanced Materials Data

Theme:
Machine Learning
Funding:
Federal Mogul, EPSRC

This project investigates the problem of classifying and predicting fatigue crack initiation sites, through microstructure quantification in Austempered Ductile Iron. The aim of this work is to build data driven classifiers that provide enhanced understanding of a system through the ability to visualise input/output relationships, as well as providing good predictive performance for a set of imbalanced data.

Primary investigators

Secondary investigator

  • Gary Lee

Associated research group

  • Information: Signals, Images, Systems Research Group
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