在Leo Breiman的理论中,第一个就是oob(Out of Bag Estimation),查阅了好多文章,并没有发现一个很好的中文解释,这里我们姑且叫他袋外估测。 01 — Out Of Bag 假设我们的训练数据集由T表示,并假设数据集具有M个特征(或属性或变量)。 T = {(X1,y1), (X2,y2), ... (Xn, yn)} Xi is input vecto...
What is the Out-of-Bag error? The OOB error is a prediction error estimation method used in machine learning models that involve bagging. It uses data samples not included in the bootstrap sample for creating the model, referred to as out-of-bag samples. How does the OOB error benefit ...
out-of-bag estimation:out-of-bag估计 下载积分: 2000 内容提示: 1 OUT-OF-BAG ESTIMATIONLeo Breiman*Statistics DepartmentUniversity of CaliforniaBerkeley, CA. 94708leo@stat.berkeley.edu AbstractIn bagging, predictors are constructed using bootstrapsamples from the training set and then aggregated to ...
1 OUT-OF-BAG ESTIMATION In bagging, predictors are constructed using bootstrap samples from the training set and then aggregated to form a bagged predictor. Each bootstrap sample leaves out about 37 % of the examples. These left-out examples can be used to form... L Breiman 被引量: 1发...
Out-of-bag estimation - Breiman - 1996 () Citation Context ...milar data sets are created by resampling with replacement (that is, bootstrapping) and regression trees are grown without pruning and averaged, the variance component of the output error is reduced (=-=Breiman 1996-=-a; ...
Interval estimation for the difference between independent proportions: comparison of eleven methods. Stat Med. 1998;17(8):873-890.PubMedGoogle ScholarCrossref 24. Callaway CW, Soar J, Aibiki M, et al; Advanced Life Support Chapter Collaborators. Part 4: advanced life support: 2015 ...
Munoz, G.M., Suarez, A.: Out-of-bag estimation of the optimal sample size in bagging. Pattern Recogn. 43 , 143–152 (2010) MATHGonzalo Martnez-Muoz , Alberto Surez, Out-of-bag estimation of the optimal sample size in bagging, Pattern Recognition, v.43 n.1, p.143-152, January,...