multi-classification fuzzy pattern recognition model 多级模糊模式识别模型
multi-classification 多元分类
multi-classification text 多类文本分类
multi-classification SVM 多分类SVM
multi-classification model 多分类模型
multi-classification methods 多类分类方法
adaboost multi-classification Adaboost多分类
In this paper, a new method which combines unsupervised and supervised learning strategy is put forward to construct the multi classification decision tree.
提出了一种融合无监督和监督两种学习策略生成多分类决策树的方法。
In the first phase, we carried out the dual classification, determine whether a syntactic component is a semantic role, then do multi-classification to assign a specific semantic role.
在第一阶段先进行二元分类，判别一个句法成分是否为语义角色，然后对第一阶段中的语义角色再进行多元分类，给其分配具体的语义角色。
We solve the multi-classification task by using a so called Coding SVM. By using this algorithm, we not only solve the classification task but also reduce the training and testing time.
采用了一种基于编码支持向量机的多分类方法，该方法解决了SVM多分类问题的同时，有效地减少了训练和测试时间，提高了算法的效率。
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