How Random Forest Performs So Well? Bias Variance Trade-Off in Random Forest
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- Опубліковано 19 лип 2021
- Understand the reason behind Random Forest's strong performance. This video explains the concept of Bias-Variance Trade-Off in Random Forest in simple terms, revealing why it's a powerful technique in machine learning.
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This guy has beaten all the ML videos on UA-cam, great piece of work
Great job mate!
Can you please start time series and it's algorithms. In many of the interviews I attended, the client expectation is that time series is a fundamental concept and one should be adroit in time series problems. Surprisingly, very few trainers on UA-cam are exploring this topic and that too just on the surface.
I request you to please start time series lectures as it's very intuitive topic and you're exceptional in explaining complex topics.
Regards
Sure Arun. Noted
Thanks for asking
Great explanation. The way you use visualization is awesome. Keep doing the same in plethora of topics.
Next Level Video , Thanks a Lot :)
Love you brother from bangladesh
excellent intution
Awesome
finished watching
best!
Will you continue making these videos after 100th day? As a lot of classical algorithms are still left to cover I think. :)
Yes all the algos will be covered
@@campusx-official
Hello Sir, XGBoost is not included in playlist, could you please make a video on XGBoost ?
But our variance comes from the test data? How is it impacted by removing the impact of outliers/noisy points from the training data?
How random forest reduces variance is not clear to me, if someone could help.
Because Weights are already calcuated for features during training
sir your video are excellent, but instead of doing in hindi can you please do it in English, it will help us lot for not understanding hindi language ,it my request
finished coding