کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
397222 1438432 2016 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Evidential calibration of binary SVM classifiers
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Evidential calibration of binary SVM classifiers
چکیده انگلیسی

In machine learning problems, the availability of several classifiers trained on different data or features makes the combination of pattern classifiers of great interest. To combine distinct sources of information, it is necessary to represent the outputs of classifiers in a common space via a transformation called calibration. The most classical way is to use class membership probabilities. However, using a single probability measure may be insufficient to model the uncertainty induced by the calibration step, especially in the case of few training data. In this paper, we extend classical probabilistic calibration methods to the evidential framework. Experimental results from the calibration of SVM classifiers show the interest of using belief functions in classification problems.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Approximate Reasoning - Volume 72, May 2016, Pages 55–70
نویسندگان
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