评价分类 meaning in Chinese
rank, classify
Examples
- Secondly , we analyse general criteria of data classification , the definition and representation method of conceptual hierarchy , and criteria of evaluating classification scheme . according to the analysis , we briefly provede the architecture of data classifier
而后，分析了数据分类的一般标准、概念层次的定义和表示方法、评价分类模式的标准等问题，并给出了数据分类器的结构框架。 - Furthermore , in order to assure that the acquired classification rules to be accuracy as well as comprehensible , we put forward a method to compute the comprehensibility of the classification rule using attribute information gain , different to the other methods which evaluate the comprehensibility of the rule only by its simplicity . thus the output of the mining is more understandable and informational . we also do it using a niche - based ga
在此基础上，为了从现有数据中挖掘易于理解的分类规则，本文提出了一种应用属性信息增益计算分类规则可理解性程度的方法，改进了以往方法中仅依靠规则的简单度来评价分类规则易于理解性的缺点，从而使得到的分类规则包含有更多的分类信息，更加有助于用户的理解。 - 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。