Bilkent CEIS DEPT 1992 Tech Report abstracts

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The file names are of the sort BU-CEIS-YYXX.ps.z 

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<A href="http://www.cs.bilkent.edu.tr/tech-reports/1992/BU-CEIS-9201.ps.z">BU-CEIS-9201</A><br>

<h3>TITLE: Prediction of Stock Market Index Changes<br>
AUTHOR(S): Izzet Sirin and H. Altay Guvenir
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ABSTRACT: Systems for inducing concept descriptions from examples 
are valuable tools for assisting in the task of knowledge 
acquisition for expert systems. In this research three machine 
learning techniques are applied to the problem of predicting the 
daily changes in the index of Istanbul Stock Market, given the 
price changes in other investment instruments such as foreign 
currencies and gold, also changes in the interest rates of 
government bonds and bank certificate of deposit accounts. 
The techniques used are Instance-Based Learning (IBL), 
Nested-Generalized Exemplars} (NGE), and Neural Networks (NN). 
These techniques are applied to the actual data comprising the 
values between January 1991 and July 1992. The most important 
characteristic of this data is the large amount of noise inherent 
in its domain. In this paper we compare these three learning 
techniques in terms of efficiency, ability to cope with noisy 
data, and human friendliness of the learned concepts.
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