基于WEKA平台的分类预测模型分析

Analysis of Classification-based Prediction Model Using WEKA Interface

详细分析了C4.5算法和基于蚁群算法的分类算法,进一步给出基于WEKA平台的预处理数据、分类模型J48的使用步骤,并在WEKA平台中嵌入基于蚁群算法的新的分类方法,最后将这两种算法应用于乳腺癌诊断,分类准确率采用10次交叉验证评价。研究结果表明:这两种算法的准确率分别是75.7%和78.5±1.25%。基于蚁群算法的分类算法的分类准确率较高,更适用于乳腺癌的诊断。

Firstly,the C4.5 algorithm and the classification algorithm based on ant colony optimization algorithm were discussed.Then,the steps of the data preprocess and J48 were given,and the classification algorithm based on ant colony optimization algorithm was added into the WEKA interface.Finally,these two algorithms were applied to diagnosis breast cancer,and the classification accuracy was assessed by 10 fold cross validation.The results show that,using these two algorithms,the accuracy rates are 75.7% and 78.5±1.25%,and the classification accuracy of the classification algorithm based on ant colony optimization algorithm is high and applicable for breast cancer diagnosis.