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。
This thesis mainly deals with the feature extraction technologies in infrared image and target multi-classification methods.
本文重点研究了红外图像目标的特征提取技术和多目标分类方法。
It's important to extract an appropriate fuzzy rules set for multi-classification problems that have fuzzy variables.
对于具有多模糊特征变量的多分类问题，自动提取适当的模糊模式识别规则集至关重要。
Finally, a method based on sub-band feature extraction and Support Vector Machine with Binary Tree Architecture (SVM-BTA) is presented for power quality disturbances multi-classification.
最后，提出了一种基于子频带特征提取和二叉树结构支持向量机相结合的电能质量多分类方法。
Finally, a method based on sub-band feature extraction and Support Vector Machine with Binary Tree Architecture (SVM-BTA) is presented for power quality disturbances multi-classification.
最后，提出了一种基于子频带特征提取和二叉树结构支持向量机相结合的电能质量多分类方法。
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