Publication Details
Knowledge Discovery in Data with FIT-Miner
Hlosta Martin, Ing. (DIFS FIT BUT)
Zendulka Jaroslav, doc. Ing., CSc. (DIFS FIT BUT)
Data mining system, data preprocessing, frequent patterns, classification, prediction, clustering
The paper deals with a data mining system FIT-Miner that has been developed at the Faculty of Information Technology of the Brno University of Technology. The system is based on a component approach where the essential functionality is encapsulated in components. A data mining task is specified graphically as a network of interconnected components. This approach makes good maintainability and scalability possible. The FIT-Miner includes components for data preprocessing, data mining and presentation of results. Implemented data mining algorithms cover all typically mined kinds of knowledge, such as frequent patterns, association rules; and classification, prediction and clustering models.
@INPROCEEDINGS{FITPUB9474,
author = "Michal \v{S}ebek and Martin Hlosta and Jaroslav Zendulka",
title = "Knowledge Discovery in Data with FIT-Miner",
pages = "182--193",
booktitle = "Znalosti 2011: Sborn\'{i}k p\v{r}\'{i}sp\v{e}vk\r{u} 10. ro\v{c}n\'{i}ku konference",
year = 2011,
location = "Star\'{a} Lesn\'{a}, SK",
publisher = "V\v{S}B-Technical University of Ostrava",
ISBN = "978-80-248-2369-0",
language = "english",
url = "https://www.fit.vut.cz/research/publication/9474"
}