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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
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how Lasso regression helps to shrinks the coefficient to zero and why ridge regression dose ...
This StatQuest video does a fantastic job of explaining in simple terms why this is the case.
1
vote
Accepted
For very simple linear regression can we quantify the prediction accuracy hit between using ...
The issue with numerical encoding in this context is you are enforcing that your input variable X is ordinal when it's likely not. This is telling your model that the order in which you encode your in …
0
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Accepted
Performing a linear regression with Perceptron
If you use a linear activation function on your perceptron you are essentially creating a linear regression where the weights connecting to your perceptron are analogous to the the coefficients on you …
2
votes
Accepted
why R-square always keep increasing
What you are trying to avoid is including features that, while they do technically improve results on your sample data, they don't do a good job of generalizing to other hold-out sets. When you say "I …