RandomizedSearchCV- Select the best hyperparameter for any Classification Model

Here we are going to have a detailed explanation of RandomizedSearchCV and how we can use it to select the best hyperparameter.
#RandomizedSearchCV

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[ijeffking]

Hello Krish, with you learning the subject of Machine Learning is a breeze. The topics you have been choosing all along have been interesting and key to remaining focussed and motivated. Thank you so much.

[kumapawa]

Thank you so much for the video, your contribution to education is invaluable. Imma pray for you!

[swathys]

Wow !! Very clearly explained Thank you so much

[himanshu]

great thanks for sharing the knowledge, it really helped

[sachincw]

Hey Krish, Thanks for the video! You could have used the object instantiated by RandomizedSearchCV Class to make the predictions instead of instantiating the Randomforest class again with the best parameters. I am just wondering why you chose to instantiate the Randomforest class again.

[lucybennett]

you didn't use Xtrain Ytrain at the end. once you find params for x and y, then do you have to fit model for Xtrain, Ytrain again, right?

[haribattula]

thanks for the video krish!! actually I expected you to explain how randomizedcv works, does it perform on all combinations that can be made from passed dict like gridsearch or it takes some random combinations to avoid increase in computational power. If that is case then what if best hyper parameter values or ignored, is it a drawback of randomized search?....

[sachink]

Hello Krish, Nice informative video. Can Randomized search CV be applied to decision tree/SVM/Logistic regression/NLP for checking hyperparameters? If yes, then the same parameter code needs to be put or different parameters should be put in that hyperparameter selection bracket?

[michellelee]

so this or grid search would be better for nltk

[ijeffking]

Krish, I have one question. While doing GridSearchCV you did not use ".values" while defining X&y.(you did not need an array). But here you have. Would you kindly explain why and when should one use ".values" in general?

[shrutijain]

Why have you used standard scaler here! We don't need it here, right?

[jitenkumarsahoo]

Hi krish, I have a query like, when I use train test split it gives good accuracy.however, when I use cross val score, it gives inconsistent accuracy for some iterations(e.g 95, 96, 96, 94, 95, 78, 63, 54, 88, 68).How will I deal this type of scenario?

[prashanthpandu]

Hello,
I have doubt that randomized serach_cv should be applied on train dataset or on whole dataset.
Can u please reply me.

[priyaprasad]

Sir can you please my doubt, if after applying randomizedsearchcv the best score is then what does it mean

[luisurena]

how would i go about it with a pipeline?

[harshgupta]

is it compulsory to do scaling for tree based algorithms?

[sreelakshmigopi]

what if we do to predict if we have more than one classification with multiple hyper parameters

[mohammadarif]

Hello Sir their is one problem that again and again when i run the randomized search cv cell every time it comes with different best score and parameters in that case what is the solution

[adityarajora]

its like grid, whats random about that????

[vaibhavchhabra]

Why is he standardizing when he is using Random Forest, which has no concept of eucledian distance?