Academic Journal

Mammography Classification by an Association Rule-based Classifier

التفاصيل البيبلوغرافية
العنوان: Mammography Classification by an Association Rule-based Classifier
المؤلفون: Osmar R. Zaiane, Maria-Luiza Antonie, Alexandru Coman
المساهمون: The Pennsylvania State University CiteSeerX Archives
المصدر: http://www.cs.ualberta.ca/~zaiane/postscript/mdmkdd02.pdf.
سنة النشر: 2002
المجموعة: CiteSeerX
مصطلحات موضوعية: KEY WORDS Mammography Mining, Image Classification, Document Categorization, Association Rules, Medical Images
الوصف: This paper proposes a new classification method based on association rule mining. This association rule-based classifier is experimented on a real dataset; a database of medical images. The system we propose consists of: a preprocessing phase, a phase for mining the resulted transactional database, and a final phase to organize the resulted association rules in a classification model. The experimental results show that the method performs well reaching over 80% in accuracy. Moreover, this paper illustrates, by comparison to other published research, how important the data cleaning phase is in building an accurate data mining architecture for image classification.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.7267; http://www.cs.ualberta.ca/~zaiane/postscript/mdmkdd02.pdf
الاتاحة: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.7267
http://www.cs.ualberta.ca/~zaiane/postscript/mdmkdd02.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
رقم الانضمام: edsbas.8E589705
قاعدة البيانات: BASE