How to impute missing data in categorical features (using MICE)

preview_player
Показать описание
Welcome to the tenth video of the series "Build your First Machine Learning Project". In this, we'll see how to impute categorical data using MICE in Python.

This video will provide in-depth information on imputing categorical data with python codes walk through.

So let's understand it.

Chapters

0:00 - 0:33 Intro
0:34- 4:52 How to impute categorical data using MICE
4:53 -8:24 Begin MICE imputation
8:24-8:40 Conclusion

Checkout Complete Machine Learning Plus Self Paced Online Courses here:

Join ML+ membership for exclusive Data science content

Previous Lesson:

Earlier Lessons:

Let me know in the comments section if you have any questions!

🤝 Like, Share, Subscribe for more!

Follow us on our social media handles for all updates, events and live sessions-

If you enjoyed this video, be sure to throw it a like and make sure to subscribe to not miss any future videos!

Thanks for watching!

#mlmodeling, #python, #machinelearning, #artificialintelligence, #pandas, #datascience
Рекомендации по теме
Комментарии
Автор

Thanks for the video.
Do you have any Idea how we can use any smart imputation technique to non-Boolean-categoricals? I have a bit of headache in doing that

alison-in
Автор

You are a genius! Your video helped me a lot! :)

sabalunax
Автор

Hello. For extremely large datasets like CERT r4.2 dataset, which technique would you recommend for filling NaN, missing values? For example, the 'activity' column? Thank you.

joguns
Автор

great video..

Some doubts-

1. Whats the intuition behind the baysian intuition. How the genders were assigned for missing places?

2. Can this be safely used for any categorical data which has missing values??

Again great work...

ketanbutte
Автор

Thank you, great video!! But shouldn't you use one hot enconding instead of label encoding because it is a nominal cat variable?

MaximoTartaglia
Автор

what is the difference of this video with Mode imputation? it did the same thing with long codes

bOOkadiOO
visit shbcf.ru