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

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Krish Naik

Krish Naik

Жыл бұрын

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
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Пікірлер: 15
@callsignkpop
@callsignkpop 9 ай бұрын
You were so much more clear than any professor or any online resource I've consulted, you're amazing!!!
@graveyard8661
@graveyard8661 Жыл бұрын
Thank you for your thorough explaination!
@oshinfrancistunde4455
@oshinfrancistunde4455 Жыл бұрын
I just join ur channel Please continue posting machine learning tutorials and advice And i have review ur formal video It was awesome i like ur explaination I hope that i will learn more before joining college
@raghavendragg9709
@raghavendragg9709 Жыл бұрын
Thank you for creating video on this topic 👍
@krishnachitrak9529
@krishnachitrak9529 Жыл бұрын
perfectly explained
@zaafirc369
@zaafirc369 Жыл бұрын
Should we use OOB error or accuracy from test dataset to validate random forest model?
@michaelho5138
@michaelho5138 Жыл бұрын
How can we be sure that after bootstrapping of the data, there will be remaining out of bag records to be used as a validating training data set? Is it not possible that you could sample all data points even with replacement when bootstrapping?
@shreyasb.s3819
@shreyasb.s3819 Жыл бұрын
I got this question in interview 1.5 years ago
@shadiyapp5552
@shadiyapp5552 Жыл бұрын
Thank you sir ♥️
@progamer0256
@progamer0256 Жыл бұрын
Sir plz continue nlp lectures attention models and transformer bert
@itsamankumar403
@itsamankumar403 6 ай бұрын
Thank you Sir :)
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@sreelakshmiv1072 Жыл бұрын
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@vijaykumbhar1657 Жыл бұрын
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@shivam_kumar_sk
@shivam_kumar_sk Жыл бұрын
First comment 🎊🎊
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