Thesis Topic Details
Topic ID: |
535 | |
Title: |
Inductive Logic Programming and Minimum Message Length Inference | |
Supervisor: |
Mike Bain | |
Research Area: |
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| Associated Staff | ||
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Assessor: |
Claude Sammut | |
| Topic Details | ||
Status: |
Active | |
Type: |
Research | |
Programs: |
CS CE BIOM BINF SE | |
Group Suitable: |
No | |
Industrial: |
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Pre-requisites: |
DN average or better | |
Description: |
The Minimum Message Length (MML) principle is a universal principle applicable in machine learning, statistics, econometrics and data mining. It is Bayesian (meaning that it takes advantage of available prior knowledge) and firmly based in information theory. In its most general form, MML can in principle be used to infer any arbitrarily complex computable function that might underly a body of data. It can be thought of as a quantitative form of Ockham's razor. In this work, we consider modelling data using logic programs, which gives us a rather rich language of which decision trees and graphs are a special case. We re-visit earlier work of Muggleton, Srinivasan and Bain (1992) which used Minimum Description Length (MDL), a related subsequent idea to MML. Several pairs of papers (Quinlan and Rivest, 1989; Wallace and Patrick, 1993) (Kearns, Mansour and Ng, 1997; Viswanathan, Wallace, Dowe and Korb, 1999) show the advantages of refining MML coding schemes. The benefits of faster machines should also be a substantial bonus in re-visiting this work. The project could be divided into at least two parts. One part of the project is concerned with optimal MML encoding - this will entail both optimal encoding of logic programs and optimal encoding of the data given the relevant logic programs. Another part of the project will concern, given a body of data, searching through the space of logic programs to find the one which minimises the length of the two-part MML message. Possible search techniques include random coding (Wallace), simulated annealing, genetic algorithms, etc. Time permitting, possible extensions to the project include inference of constraint logic programs. |
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Comments: |
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| Past Student Reports | ||
| No Reports Available. Contact the supervisor for more information.
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