CSC423 Learning and prediction Semester 2 1999

Course Outline:
Topics include: elementary information theory (including noiseless coding and Huffman codes); elementary foundations of inductive inference; introduction to Minimum Message Length (MML) inference; MML approaches to clustering, unsupervised classification, decision trees, causal modelling, data mining. Applications to be considered include: image compression, models of protein folding, bushfire prediction, DNA alignment and the human genome project, authorship identification for texts, etc.

Lectures:
Thursdays 3.00 - 5.00pm (S15)

Lecturers:
Dr David Dowe, room 103 building 26, ext 55 776, email: dld@cs.monash.edu.au
Dr Lloyd Allison, room 109 building 26, ext 55 205, email: lloyd@cs.monash.edu.au

Assessment:
Assignment 1 (LA) - due Week 6 (20%)
Assignment 2 (DLD) - due Week 11 (30%)
Examination (50%)

Lecture Material:
http://www.cs.monash.edu.au/~lloyd/tilde/CSC4/CSE423/index.html contains notes for this course.

Back to 1999 Honours subjects