کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1145028 | 957446 | 2009 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
D-optimality criterion for weighting variables in K-means clustering
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: D-optimality criterion for weighting variables in K-means clustering D-optimality criterion for weighting variables in K-means clustering](/preview/png/1145028.png)
چکیده انگلیسی
The aim of the study is how to achieve best K-means clustering structure so that k groups uncovered reveal more meaningful within-group coherence by assigning weights w1,â¦,wm to m clustering variables Z1,â¦,Zm. We propose Wilks' lambda as a criterion to be minimized with respect to variable weights w1,â¦,wm. This criterion, that is the ratio of the determinant of the within-cluster sums of squares and cross products matrix and that of the between clusters sums of squares and cross products matrix, is equivalent to the D-optimality criterion in the optimal design theory and related to minimization of the volume of the simultaneous confidence region of the cluster means. We will present the computing algorithm for such K-means clustering and numerical examples, among which one is simulated, two are real and the other one is the real data set augmented with additional simulated noise variables.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of the Korean Statistical Society - Volume 38, Issue 4, December 2009, Pages 391-396
Journal: Journal of the Korean Statistical Society - Volume 38, Issue 4, December 2009, Pages 391-396
نویسندگان
Yong B. Lim, Yeo Jung Park, Myung-Hoe Huh,