structured classifier meaning in Chinese
结构化类元
Examples
- Ear recognition based on compound structure classifier
基于主元分析与支持向量机的人脸识别方法 - Based on the research of ear recognition with independent component analysis ( ica ) , a new compound structure classifier ( cscer ) ear recognition model was proposed
摘要在基于独立分量分析的人耳识别方法研究基础上，提出复合结构分类器的人耳识别通用模型。 - This is the result of the reasons are : representative estimates of the number of structure classifiers the match capacity constraints and representative estimates of the number of structure is the indicator of grammar significance
造成这一情况的原因是：表约量的数量结构中量词本身的搭配能力限制以及表约量的数量结构自身具有的特指的语法意义。 - ( 2 ) the influence to classification result is highly effected by using different classifier , for example , the center - vector algorithm obtains better classification results than other two algorithms . with the character feature , the average recall is 80 . 73 % , and the average precision is 82 . 94 % , and with the chinese - word feature , the average recall is 83 . 6 % , and the average precision is 85 . 97 % . different corpuses influence the classification result . for example , the average recall is 89 . 31 % and the average precision is 88 . 33 % , by using the news web pages as corpus from the web site " www . sina . com . cn " , which adopt the center - vector algorithm to structure classifier and select chinese - word as feature
对三种分类器分别以字、词为特征进行分类测试、分析发现：使用相同的分类算法，用词作为特征项，比以字作为特征的分类效果好；用不同的算法构造分类器对分类效果的影响很大，如中心向量算法在字、词特征下的分类效果优于其他两算法；在以字为特征的情况下，该算法的平均查全率80 . 73 ，平均查准率82 . 94 ；在以词为特征的情况下，该算法的平均查全率83 . 6 ，平均查准率85 . 97 ；选用语料不同对分类效果也有影响，如用新浪网( www . sina . com . cn )网页语料进行测试，使用中心向量法分类器和词作为特征的情况下，平均准确率为89 . 31 ，平均查全率为88 . 33 。 - My main work is as following : 1 ) applying feature mapping , sub - band structure classifier and multi - classifier cooperation to enhance the robust of system ; 2 ) giving out close - set fusion and open - set fusion functions to solve the problems of speaker identification and verification respectively ; 3 ) building the dynamic recognition length algorithm based on optimal stopping rules ; 4 ) developing a applied system based on the techniques above
主要工作是： 1 、提出参数映射、子带结构分类器和多分类器系统以提高系统的鲁棒性能； 2 、给出证据融合的闭集公式和开集公式，它们分别适用说话人辨认和确认问题的； 3 、通过最优停止理论建立识别长度自适应算法； 4 、开发了一个实用的说话人识别系统。