Out Of Bag Evaluation(OOB) And OOB Score Or Error In Random Forest скачать в хорошем качестве

Out Of Bag Evaluation(OOB) And OOB Score Or Error In Random Forest

Out-of-bag (OOB) error, also called out-of-bag estimate, is a method of measuring the prediction error of random forests, boosted decision trees, and other machine learning models utilizing bootstrap aggregating (bagging). Bagging uses subsampling with replacement to create training samples for the model to learn from. OOB error is the mean prediction error on each training sample xi, using only the trees that did not have xi in their bootstrap sample ------------------------------------------------------------------------------------------------------- Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more    / @krishnaik06   Please do subscribe my other channel too    / @krishnaikhindi   Connect with me here: Twitter:   / krishnaik06   Instagram:   / krishnaik06