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决策树学习笔记整理。通过训练数据构建决策树,可以高效的对未知的数据进行分类。上面公式实际上就是当前节点的不纯度减去子节点不纯度的加权平均数,权重由子节点记录数与当前节点记录数的比例决定。噪音数据:训练数据中存在噪音数据,决策树的某些节点有噪音数据作为分割标准,导致决策树无法代表真实数据。这样可以用具有最小错误率对应的i... 阅194 转6 评0 公众公开 15-03-31 11:56 |
Both Gradient-Boosted Trees (GBTs) and Random Forests are algorithms for learning ensembles of trees, but the training processes are different.Increasing the number of trees will decrease the variance in predictions, improving the model’s test-time accuracy. Training time increases roughly linearly in the number of t... 阅122 转0 评0 公众公开 15-03-30 14:06 |