集成学习：随机森林、GBDT、XGBoost实战代码合集.zip

[{"title":"（ 9 个子文件 213KB ） 集成学习：随机森林、GBDT、XGBoost实战代码合集.zip","children":[{"title":"02_Adaboost案例一：Adaboost分类算法.ipynb <span style='color:#111;'> 54.90KB </span>","children":null,"spread":false},{"title":"-1. Bagging&Boosting算法应用在回归模型中.ipynb <span style='color:#111;'> 6.98KB </span>","children":null,"spread":false},{"title":"datas","children":[{"title":"boston_housing.data <span style='color:#111;'> 47.93KB </span>","children":null,"spread":false},{"title":"yinzi.csv <span style='color:#111;'> 591B </span>","children":null,"spread":false},{"title":"newdata.csv <span style='color:#111;'> 176.32KB </span>","children":null,"spread":false},{"title":"iris.data <span style='color:#111;'> 4.44KB </span>","children":null,"spread":false},{"title":"risk_factors_cervical_cancer.csv <span style='color:#111;'> 99.67KB </span>","children":null,"spread":false}],"spread":true},{"title":"03_Adaboost案例二：Adaboost API algorithm参数取值比较.ipynb <span style='color:#111;'> 72.91KB </span>","children":null,"spread":false},{"title":"01_随机森林案例一：宫颈癌预测.ipynb <span style='color:#111;'> 134.87KB </span>","children":null,"spread":false}],"spread":true}]