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Metaheuristic Methods for Probabilistic Graphical Models

Cardiff School of Mathematics

About the Project

Metaheuristic Methods for Probabilistic Graphical Models

The aim of this project is to develop approaches for learning probabilistic graphical models that can be used for classification problems and to explore causal relationships between attributes.

- The candidate will develop new algorithms for the problem of learning probabilistic graphical models.
- The candidate will develop a variety of performance metrics to evaluate the performance of his/her algorithms based on datasets from the UCI Machine Learning repository.
- The candidate will carry out a detailed experimental analyses of the approaches.
The output of the work will have a direct and immediate impact Cardiff University’s collaboration with the local health boards. Here, existing Machine Learning methods have already been tested in a variety of patient classification problems.


Applicants should submit an application for postgraduate study via the online application service:

Funding Notes

In the research proposal section of your application, please specify the project title and supervisors of this project and copy the project description in the text box provided.

We are interested in pursuing this project and welcome applications if you are self-funded or have funding from other sources, including government sponsorships or your employer.

In the funding section, please select the ’self -funding’ option and specify the project title

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