کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
532553 869968 2010 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Supervised feature selection by clustering using conditional mutual information-based distances
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Supervised feature selection by clustering using conditional mutual information-based distances
چکیده انگلیسی

In this paper, a supervised feature selection approach is presented, which is based on metric applied on continuous and discrete data representations. This method builds a dissimilarity space using information theoretic measures, in particular conditional mutual information between features with respect to a relevant variable that represents the class labels. Applying a hierarchical clustering, the algorithm searches for a compression of the information contained in the original set of features. The proposed technique is compared with other state of art methods also based on information measures. Eventually, several experiments are presented to show the effectiveness of the features selected from the point of view of classification accuracy.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 43, Issue 6, June 2010, Pages 2068–2081
نویسندگان
, ,