Finally, we use standard data sets to test the classification results and the results are evaluated by precision, recall and F1.
最后,使用标准数据集对网页主题分类的效果进行了测试,并根据精确率、召回率和F1值对分类效果进行评价。
Aiming at the deficiency of evaluating classifier combination methods with standard data sets, a new classifier simulation algorithm was proposed.
针对标准数据集在评估多分类器系统的组合方法时存在的不足,设计了一种新的分类器模拟算法。
It is tested on the UCI standard data sets and compared with AIRS and the other classical classifiers. The aim is to research the performance of classifier based on artificial immune network.
在UCI标准数据集合上进行测试,与airs和其他传统分类器进行比较,目的是研究基于人工免疫网络原理的数据分类方法的性能。
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