Data MiningFor a good introduction to data mining, read this booklet from the American data mining company, Two Crows.
Down load the pdf
We will be using a free software package called Weka for the practical work and the assignment.
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There are several data mining books in the library. These ones are worth a look.
- Data Mining: Practical Machine Learning Tools and Techniques by I.H. Witten and E. Frank
- Berry , M.J.A., Linoff, G.S. (1997 1 st ed/2004 April 2 nd ed) Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management , Wiley
- Data mining : concepts and techniques / Jiawei Han [and] Micheline Kamber. San Francisco ; London : Morgan Kaufmann Publishers, c2001
Go to the statistics tutorial
Bayesian NetworksBefore you start this part of the course, make sure you understand the basic concepts of probability. There will be a lecture on the subject, but you will find it all easier if you already know how to calculate the probability of a certain event. If you cannot quickly answer the following questions, then you need to do a bit of preparation:
- What is the probability of picking a red card from a deck of 52 playing cards?
- What is the probability of picking a spade from a deck of 52 playing cards?
- What is the probability of picking an ace from a deck of 52 playing cards?
- What is the probability of picking a red ace from a deck of 52 playing cards?
- What is the probability of picking two red cards in a row from a deck of 52 playing cards?
There are several copies of the textbook for this course in the RBR.
Korb, K.B., Nicholson, A.E. (2004) Bayesian Artificial Intelligence, Chapman & Hall/CRC
Chris Bishop has a very good (if a little challenging) book called Pattern Recognition and Machine Learning. You can see some things about it here:
The sample chapter is about Bayesian networks, amongst other things.
We will be using a free software package called Netica for the practical work
Download Netica Software