Pattern classification by learning from example and extension matrix
Yong-Ge Wu, Jingyu Yang, Lei-Jian Liu, Ke Liu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
Sometimes the classifiers based on the features extracted from patterns may not be robust, in this case, to obtain better classification results, man's interruption is needed, then subjectivity and uncertainty due to man's action are followed as a result. In this paper, an algorithm able to automatically create a classifier is provided by the technique of learning from examples, with which pattern recognition, such as the facial images recognition, are completed.