کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
505727 864532 2009 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Hedged predictions for traditional Chinese chronic gastritis diagnosis with confidence machine
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Hedged predictions for traditional Chinese chronic gastritis diagnosis with confidence machine
چکیده انگلیسی

Most classifiers output predictions for new instances without indicating how reliable they could be. Transductive confidence machine (TCM) is a novel framework that provides hedged prediction coupled with valid confidence. Many popular machine learning algorithms can be transformed into the framework of TCM, and therefore be used for producing hedged predictions. This paper incorporates random forest (RF) to propose a method named TCM-RF for classification of chronic gastritis data. Our method benefits from TCM-RF's high performance when features are noisy, highly correlated and of mixed types. The experimental results show that TCM-RF produces informative as well as effective predictions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 39, Issue 5, May 2009, Pages 425–432
نویسندگان
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