A Flexible Classifier for Hibernal Trees
Hongjun Diao, Yijun Chen, Fei Zhu · 2008
Auto tree classification is of use in plant research. We put forward and implement a hibernal tree automatic classification system. In the paper features of tree system and other aspects that could influence classification results are analyzed and taken into consideration in classifier modeling. We extract the most related contents and information for classification, set up hibernal trees classification model, and finally accomplish a hibernal tree automatic classification system based on Bayes. We also make use of Bayes Network in coefficient learning so as to get best classification effects by adaptive self-learning and necessarily adjusting parameters according to actual data. Experiment result shows the method proposed in the paper can well solve hibernal tree automatic classification problems.