کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1181755 | 962985 | 2006 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Auto-associative Multivariate Regression Trees for Cluster Analysis
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Multivariate Regression Trees, an intuitive and simple regression technique, intrinsically produce homogenous subsets of data. These characteristics imply that Multivariate Regression Trees have the potential to be utilised as an easily interpretable clustering method. The suitability of Multivariate Regression Trees as a clustering technique is investigated with two real datasets containing only explanatory variables. The preliminary results show that Multivariate Regression Trees as a clustering algorithm produce clusters of similar quality to the well-known K-means technique, and more recent approaches to Cluster Analysis including Mixture Models of Factor Analysers and Plaid Models. The study also evaluates the suitability of various criteria used to describe cluster solutions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 80, Issue 1, 20 January 2006, Pages 120-129
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 80, Issue 1, 20 January 2006, Pages 120-129
نویسندگان
Christine Smyth, Danny Coomans, Yvette Everingham, Timothy Hancock,