The GUHA Method in Data Mining
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Tiedostot
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URN:
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http://URN.fi/URN:NBN:fi:tty-201209261292
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Nimeke:
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The GUHA Method in Data Mining |
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Tekijä:
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Turunen, Esko |
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Julkaisun tyyppi:
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Esitelmä - Presentation |
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Julkaisuaika:
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2012 |
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Yliopisto:
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Tampereen teknillinen yliopisto - Tampere University of Technology |
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Tiedekunta:
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Luonnontieteiden ja ympäristötekniikan tiedekunta – Faculty of Science and Environmental Engineering |
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Laitos:
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Matematiikan laitos – Department of Mathematics |
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Tiivistelmä:
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Knowledge discovery in databases (KDD) is the process of identifying valid, novel, potentially useful, and ultimately understandable patterns in (often huge) datasets. Data mining is the central step of KDD: the application of computational techniques to find patterns. GUHA is one of the original data mining methods and is based on a special extension of classical logic. In this course we study the mathematical foundations of the GUHA method and LISp-Miner, a computer implementation of GUHA, and look at several real world applications.
1. Does my data contain something interesting?
2. GUHA produces hypotheses
3. GUHA is a logic-theory based approach to data mining
4. More about the foundations of GUHA
5. Introduction to LISp-Miner software
6. The 4ftTask module
7. 4ftTask module continued
8. Statistical quantifiers in 4ftTask
9. Differences between sets
10. Action Miner |
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Tekijänoikeudet:
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This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited. |
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