کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1149027 | 957860 | 2012 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Model-based clustering, classification, and discriminant analysis of data with mixed type
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
We propose a mixture of latent variables model for the model-based clustering, classification, and discriminant analysis of data comprising variables with mixed type. This approach is a generalization of latent variable analysis, and model fitting is carried out within the expectation-maximization framework. Our approach is outlined and a simulation study conducted to illustrate the effect of sample size and noise on the standard errors and the recovery probabilities for the number of groups. Our modelling methodology is then applied to two real data sets and their clustering and classification performance is discussed. We conclude with discussion and suggestions for future work.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 142, Issue 11, November 2012, Pages 2976–2984
Journal: Journal of Statistical Planning and Inference - Volume 142, Issue 11, November 2012, Pages 2976–2984
نویسندگان
Ryan P. Browne, Paul D. McNicholas,