The Classification Based on Evidence Theory in Medical Data Mining
Publish place: 2nd Iran Data Mining Conference
Publish Year: 1387
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
IDMC02_131
تاریخ نمایه سازی: 14 فروردین 1388
Abstract:
Studies have revealed that a combination of classifiers is often more accurate than an individual classifier. In this paper we propose a new method for combination of multiple classifiers using Dempster-Shafer theory of evidence combination for mining medical data. We combine the beliefs of three classifiers:Decision Tree,K-Nearest Neighbor and Naïve Bayesian.Our experiments over the Wisconsion Breast Canser dataset shows that out approach has better accuracy than any individual classifier. In addition the performance of our suggested method is better than similar method and weighted linear and majority vote combination models.
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