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Classification of Imbalanced Materials Data

Projects

Other Machine Learning Projects

Other EPSRC Funded Projects

musicSpace: using and evaluating e-Science Design Methods and Technologies to Improve Access to Heterogeneous Music Resources fo
Implementation of Ignition Unit for Liquid Pulsed Plasma Thrusters

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.

Type: Postgraduate Research
Research Group: Information: Signals, Images, Systems Research Group
Theme: Machine Learning
Dates: ? to ?

Funding

Federal Mogul
EPSRC

Principal Investigators

[hidden]
Dr Philippa Reed
Professor Steve R Gunn

Other Investigators

Gary Lee

URI: http://id.ecs.soton.ac.uk/project/236
RDF: http://rdf.ecs.soton.ac.uk/project/236

More information

You can edit the record for this project by visiting http://secure.ecs.soton.ac.uk/db/projects/editproj.php?project=236