کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9651759 | 1438537 | 2005 | 22 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Effective dimensions of partially observed polytrees
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Effective dimensions of partially observed polytrees Effective dimensions of partially observed polytrees](/preview/png/9651759.png)
چکیده انگلیسی
Model complexity is an important factor to consider when selecting among Bayesian network models. When all variables are observed, the complexity of a model can be measured by its standard dimension, i.e., the number of linearly independent network parameters. When latent variables are present, however, standard dimension is no longer appropriate and effective dimension should be used instead [Proc. 12th Conf. Uncertainty Artificial Intell. (1996) 283]. Effective dimensions of Bayesian networks are difficult to compute in general. Work has begun to develop efficient methods for calculating the effective dimensions of special networks. One such method has been developed for partially observed trees [J. Artificial Intell. Res. 21 (2004) 1]. In this paper, we develop a similar method for partially observed polytrees.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Approximate Reasoning - Volume 38, Issue 3, March 2005, Pages 311-332
Journal: International Journal of Approximate Reasoning - Volume 38, Issue 3, March 2005, Pages 311-332
نویسندگان
Tao Chen, TomáÅ¡ KoÄka, Nevin L. Zhang,