Correlation Matrix (Numerical) | Feature Selection | Python

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⭐️ Content Description ⭐️
In this video, I have explained on how to perform feature selection using correlation matrix for numerical attributes. We can find the dependent variables for the target variable. We can also eliminate unnecessary features from the dataset.

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Комментарии
Автор

could you please explain how dimension reduction done using best first search with an example of correlation matrix .

sweetyrani
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HI Aswin bro, what does it meant the term you used "its leaking the data" @4.48 sec.

tinytrip
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hi aswin bro, values more than 0.05? or more than 0.5 corr dependies with each other? @9.05 sec

tinytrip
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By doing feature selection with the correlation matrix, we may ignore interactions between features that were not captured by this method.

MrRafaelSencio
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What should we do with -ve correlated columns?

karthikrajendran
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Hi, Video did not clearly say, which column to drop and which one to keep. No conclusion. More info could be better

vijaynath