کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
531309 | 869827 | 2009 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Integrating prior domain knowledge into discriminative learning using automatic model construction and phantom examples Integrating prior domain knowledge into discriminative learning using automatic model construction and phantom examples](/preview/png/531309.png)
Domain knowledge captures an expert's approximate understanding of the world, its objects, and their properties. When available, it should serve to augment the information in a classification learner's training set. But this form of prior knowledge does not easily fit into the statistical learning paradigm. We propose and evaluate the use of phantom examples to remedy this. Our system performs automated model construction and learns generative models for phantom examples that adapt to the need of individual tasks. The approach is validated on the challenging real-world task of distinguishing handwritten Chinese characters. The approach improves learning significantly, provides additional robustness, and works well even though the domain knowledge is imperfect and approximate.
Journal: Pattern Recognition - Volume 42, Issue 12, December 2009, Pages 3231–3240