How To Handle Missing Values in Categorical Features

Hello All here is a video which provides the detailed explanation about how we can handle the missing values in categorical values

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[soumikchakraborty]

You are just awesome bro. Please make a video on AIC, AUC, ROC curve.

[pallabsaha]

Very well explained. If you could show the same on a dataset and code that would be very helpful. Thank you sir for your videos. Love them all.

[gabrielburgos]

You are the MVP, when no one has the answer, you do.

[aksontv]

Finally got right man to learn data science and ML. Thank you sir!

[duvanmartinez]

Great work, you're awesome, you're the best youtuber I've found.

[chimadivine]

This is just awesome, Krish. Thanks so much!

[mohitupadhayay]

This was such an amazing life saver. I didn't even knew I had this question and the video just popped up.
Didn't find this tutorial anywhere else.

[doop]

I was stuck for days trying to figure out how to predict missing data using ML. This helped me understand so so so much better! 😍 Thank you so much!! 🙏💚

[AmitYadav-igyt]

Sir, U took data set which has a missing value in just one column. You told about Predicting missing value my using other columns as Training set. Let's say we have a data set in which every columns have some missing values..In such case which columns should be use to predict missing values?

[tumul]

thank you sir ! amazing video as always

[amedyasar]

it was quite short explaination and nice points to undersdtand.
Tanks!

[abinashkumarsinha]

This helped me a lot in my project work. Very useful and very well explained.

[out_aloud]

Hello sir, maybe I am here too late but I still hope that you would acknowledge this question as it might be of immense value. I have a disputed question which basically revolves around knn imputer, scaling and the concept of data leakage. As the knn imputer works on the principles same as knn algo, it does share the pros and cons of knn algo, right. So wont it be better to simply scale the data first ? Also, in case I am separating out the train and test data in order to avoid data leakage, should I split the data and then scale, impute ? Or should I impute and then split, scale it ? In case I split first...which is the most common preference which stats should I use for the user input. And lastly how should I handle the label encoded columns if any ? Nobody is discussing on this when it is one of the most imp problems a person would likely face. Can you please make a video on this ?

[sandyjust]

Great explanation of the concept. With unsupervised technique we might be in situation that both male and female falls under group 2. Then what would our approach?

[divyaharshad]

For technique 3 will it lead to multicollinearity in the data?

[MegaJaivardhan]

love you bro.. could you make a video AUC and ROC curve?

[saurabhpathare]

I am always reluctant to delete or use mode for categorical values. This video explains a lot. Good approach! In technique 3, which classifier do you recommend for best efficiency?

[ankurbanerji]

Great explanation sir! Can you explain how to handle the missing values for multiple columns in a dataset

[Saikrishna-lxit]

Hi bro can you make one end to end chatbot video using rasa nlu, which is useful for all who are interested in nlp.

[sandeepnallala]

doing a great work Krish. thanks a lot. Loved your Videos : )