意思就是,oob是test error的一个无偏估计. 一句话总结下: 假设Zi=(xi,yi) The out-of-bag (OOB) error is the average errorfor each Zi calculated using predictions from the trees that do not contain Ziin their respective bootstrap sample. This allows the RandomForestClassifier to be fit and v...
随机森林中的 out of bag error [译者按]:这篇文献主要翻译自参考文献[1],在 oob 部分,使用 文献[2]稍作说明。 训练数据集为 T ,具有 M 个特征 T = {(X1,y1), (X2,y2), ... (Xn, yn)} Xi {xi1, xi2, ... xiM},是输入向量 yi 是标签. 随机森林总结: 随机森林算法是一个分类器算法...
Mitchell MW (2011) Bias of the Random Forest out-of-bag (OOB) error for certain input parameters. Open Journal of Statistics 1: 205-211. doi: 10.4236/ojs.2011.13024.Mitchell, M. W. 2011. Bias of the random forest out-of-bag (OOB) error for certain input parameters. - Open J. Stat...
https://stackoverflow.com/questions/25153276/difference-of-prediction-results-in-random-forest-model https://stats.stackexchange.com/questions/412479/difference-between-the-out-of-bag-error-and-the-predicted-error 用R语言算random forests的时候发现,训练数据的model$predictions不等于predict(model, train_da...
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...
On the overestimation of random forest's out-of-bag error The ensemble method random forests has become a popular classification tool in bioinformatics and related fields. The out-of-bag error is an error estimation technique often used to evaluate the accuracy of a random forest and to select...
The hierarchical clustering results were further supported by the supervised random forest classifier, which yielded an overall out-of-bag error score of 3.4%. These results suggest that surface material regulated the functional traits of surface microbiomes, with microbes from the same material ...
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To test the quality of function f, we evaluate the mean-squared error (MSE) on the last point of every time series on that target gene. The Random Forest uses bootstrap aggregation, where each new tree is trained on a sub-sample of the training data points. The Out-of-Bag error for...
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