Handwritten Digit, Recognition Road to Contest victory

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...

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Bibliographic Details
Published in2007 IEEE Symposium on Computational Intelligence and Data Mining pp. 491 - 498
Main Authors Jankowski, Norbert, Grabczewski, Krzysztof
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2007
Subjects
Algorithm design and analysis
Classification algorithms
Computational intelligence
Data analysis
Data mining
Handwriting recognition
Informatics
Pixel
Testing
World Wide Web
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Summary: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
ISBN:1424407052
9781424407057
DOI:10.1109/CIDM.2007.368915