分类测试 meaning in Chinese
cla test
class test
Examples
- Benchmark tests are launched in the paper , and also give its compares and analysis
最后给出标准测试集的分类测试结果，并对其进行了比对、分析和讨论。 - The validity of the proposed algorithm is proved through the test on some databases of the uci repository
对uci数据库的分类测试体现了该粗糙集数据分析算法的有效性。 - ( 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 。