pd.get_dummies silently introduces multicollinearity in your data. In this tutorial, we will walk through a simple example on how you can deal with the multicollinearity by using pd.get_dummies(drop_first=True) and also by using Lasso regression. Linear Regression assumes the features to exhibit no multicollinearity so treating it is an important step in machine learning model building process. If you do have any questions with what we covered in this video then feel free to ask in the comment section below & I'll do my best to answer those. If you enjoy these tutorials & would like to support them then the easiest way is to simply like the video & give it a thumbs up & also it's a huge help to share these videos with anyone who you think would find them useful. Please consider clicking the SUBSCRIBE button to be notified for future videos & thank you all for watching. You can find me on: GitHub - https://github.com/bhattbhavesh91 Medium - https://medium.com/@bhattbhavesh91 #get_dummies #multicollinearity #cateogricaltonumeric #MachineLearning #ML #DataScience #Python
How to tackle Multicollinearity in Categorical Data | Dummy Variables | pd.get_dummies() - YouTube |
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| Education | Upload TimePublished on 20 Mar 2019 |
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