摘要
本文对混凝土的抗压强度的数据采用决策树、Boosting、随机森林、人工神经网络、支持向量机这五种方法进行建模,采用十折交叉验证评价预测精度。发现随机森林法具有较好的预测效果。
In this paper, the data of compressive strength of concrete are modeled by decision tree, boosting, random forest, artificial neural network and support vector machine methods. Ten-fold cross-va- lidation is adopted to assess the performance of these methods in terms of the prediction accuracy. It is seen that the Random Forest method has the best performance in general.
出处
《统计学与应用》
2017年第1期1-6,共6页
Statistical and Application