کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
384118 660841 2012 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Linear separability and classification complexity
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Linear separability and classification complexity
چکیده انگلیسی

We study the relationship between linear separability and the level of complexity of classification data sets. Linearly separable classification problems are generally easier to solve than non linearly separable ones. This suggests a strong correlation between linear separability and classification complexity. We propose a novel and simple method for quantifying the complexity of the classification problem. The method, which is shown below, reduces any two class classification problem to a sequence of linearly separable steps. The number of such reduction steps could be viewed as measuring the degree of non-separability and hence the complexity of the problem. This quantification in turn can be used as a measure for the complexity of classification data sets. Results obtained using several benchmarks are provided.


► Relationship between linear separability degree and complexity level of a data set.
► Quantification of the complexity of a classification problem.
► Transformation of non linearly separable problems into linearly separable ones.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 39, Issue 9, July 2012, Pages 7796–7807
نویسندگان
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