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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jankowski, N. Grabczewski, K. |
| Copyright Year | 2007 |
| Description | Author affiliation: Dept. of Informatics, Nicolaus Copernicus Univ., Torun (Jankowski, N.; Grabczewski, K.) |
| Abstract | With growing amount of data gathered nowadays, need for efficient data mining methodologies is getting more and more common. There is a large number of different classification algorithms, but choosing the best one for given data is still a difficult task. Thanks to different data mining contests we can gather lots of meta level information about classification problems and strategies leading to optimal (or close to optimal) solutions. One of the contests was organized in parallel with the ICAISC'06 conference held in Zakopane. We took part in it, and our model classified the test data with the highest accuracy. The process which led to the winner model was not simple t required multiaspect analysis of the data and different algorithms (from the point of view of suitability to the data). This article presents our road to the winner model with numerous comments on both successful and unsuccessful efforts. It also presents our model testing methodology, which always plays important role in the pursuit of accurate and well generalizing models |
| Starting Page | 491 |
| Ending Page | 498 |
| File Size | 8177384 |
| Page Count | 8 |
| File Format | |
| ISBN | 1424407052 |
| DOI | 10.1109/CIDM.2007.368915 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-03-01 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Handwriting recognition Data analysis World Wide Web Classification algorithms Data mining Informatics Pixel Computational intelligence Testing |
| Content Type | Text |
| Resource Type | Article |
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