کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4946899 1439559 2017 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning
چکیده انگلیسی
In this paper, we introduce taxonomies for similarity and dissimilarity measures, respectively, based on their mathematical properties. Further, we propose a definition for rank equivalence of (dis)similarities regarding given data for prototype based methods. Starting with this definition we provide a measure to judge the degree of equivalence, which can be used to compare respective measures as well as to consider the influence of data preprocessing regarding a single (dis)similarity measure. In the last part of the paper an adaptive mixture approach of (dis)similarity measures for improved classification learning is presented.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 268, 13 December 2017, Pages 42-54
نویسندگان
, , , ,