setting feed meaning in Chinese
给料口调节
Examples
- The optimized feature set feeds a 3 - class classification module , which is based on the traditional binary svm classifier . and the proposed linear programming svm reduces the burden of the svm classifier and improves its learning speed and classification accuracy . a new algorithm that combined svm with k nearest neighbor ( knn ) is presented and it comes into being a new classifier , which can not only improve the accuracy compared to sole svm , but also better solve the problem of selecting the parameter of kernel function for svm
在研究了数据挖掘、支持向量机及其有关技术的基础上，建立了实现三类水中目标识别的svm方法；采用线性规划svm解决了传统二次规划svm在海量样本情况下导致的时间和空间复杂度问题；提出了将最近邻分类与支持向量机分类相结合的svm - knn分类器应用于水中目标识别的思想，较好地解决了应用支持向量机分类时核函数参数的选择问题，取得了更高的分类准确率。 - In further research , the following issues must be considered : 1 ) the standardize of corpus ; 2 ) improve the accuracy of chinese words divided syncopation system , handle the different meanings of one word and recognize the words that do not appear in the dictionary ; 3 ) process semantic analysis ; 4 ) dynamically update the training sets fed back by the user ; 5 ) quantitatively analyze the system performance influenced by different factors , use an appropriate model to compare and evaluate the web text classification system ; 6 ) natural language process ; 7 ) distinguish the disguise of sensitive words
在以后的工作中考虑如下问题: 1 )数据集的标准化; 2 )分词系统精度的提高，对歧义处理以及未登录词识别的能力的提高: 3 )进行合理的语义分析: 4 )利用用户反馈信息动态更新训练集; 5 )定t分析分类器不同要素对分类系统性能的影响，使用合适的模型来比较和评价分类系统; 6 )自然语言理解问题，如“引用”问题; 7 )对于敏感词汇伪装的识别问题。