Academic Journal
Considering re-occurring features in associative classifiers
| العنوان: | Considering re-occurring features in associative classifiers |
|---|---|
| المؤلفون: | Rafal Rak, Wojciech Stach, Osmar R Zaϊane, Maria-Luiza Antonie |
| المساهمون: | The Pennsylvania State University CiteSeerX Archives |
| المصدر: | http://webdocs.cs.ualberta.ca/%7Ezaiane/pub/pakdd05.pdf. |
| بيانات النشر: | Springer |
| سنة النشر: | 2005 |
| المجموعة: | CiteSeerX |
| الوصف: | The classification problem is one of the most common tasks in Data Mining and Machine Learning. Given its vast applicability in many real domains, supervised classification has been addressed and extensively studied. There are numerous different classification methods; among the many we can cite associative classifiers. This newly suggested model uses association rule mining to generate classification rules associating observed features with class labels. Given the binary nature of association rules, these classification models do not take into account repetition of features when categorizing. Repetitions of features are often good indicators and discriminators of classes, in particular for text or other multimedia. In this paper, we enhance the idea of associative classifiers with associations with re-occurring items and show that this mixture produces a good model for classification when repetition of observed features is relevant in the data mining application at hand. |
| نوع الوثيقة: | text |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1050.1120; http://webdocs.cs.ualberta.ca/%7Ezaiane/pub/pakdd05.pdf |
| الاتاحة: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1050.1120 http://webdocs.cs.ualberta.ca/%7Ezaiane/pub/pakdd05.pdf |
| Rights: | Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
| رقم الانضمام: | edsbas.951AC2B8 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |