Difference between revisions of "Elastic Net Regression"
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
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| − | [ | + | [https://www.youtube.com/results?search_query=Elastic+Net+Regression+artificial+intelligence YouTube search...] |
| − | [ | + | [https://www.google.com/search?q=Elastic+Net+Regression+machine+learning+ML ...Google search] |
* [[AI Solver]] | * [[AI Solver]] | ||
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* [[Regularization]] | * [[Regularization]] | ||
** [[Ridge Regression]] | ** [[Ridge Regression]] | ||
| − | *** [ | + | *** [https://towardsdatascience.com/ridge-and-lasso-regression-a-complete-guide-with-python-scikit-learn-e20e34bcbf0b Ridge and Lasso Regression: A Complete Guide with Python Scikit-Learn | Saptashwa - Towards Data Science] |
** [[Lasso Regression]] | ** [[Lasso Regression]] | ||
* [[Math for Intelligence]] | * [[Math for Intelligence]] | ||
* [[Overfitting Challenge]] | * [[Overfitting Challenge]] | ||
| − | Elastic-Net Regression is combines Lasso Regression with Ridge Regression to give you the best of both worlds. It works well when there are lots of useless variables that need to be removed from the equation and it works well when there are lots of useful variables that need to be retained. And it does better than either one when it comes to handling correlated variables. [[ | + | Elastic-Net Regression is combines Lasso Regression with Ridge Regression to give you the best of both worlds. It works well when there are lots of useless variables that need to be removed from the equation and it works well when there are lots of useful variables that need to be retained. And it does better than either one when it comes to handling correlated variables. [[https://statquest.org/video-index/ StatQuest] |
<youtube>1dKRdX9bfIo</youtube> | <youtube>1dKRdX9bfIo</youtube> | ||
Revision as of 10:41, 28 March 2023
YouTube search... ...Google search
- AI Solver
- Capabilities
- Regression Analysis
- Regularization
- Math for Intelligence
- Overfitting Challenge
Elastic-Net Regression is combines Lasso Regression with Ridge Regression to give you the best of both worlds. It works well when there are lots of useless variables that need to be removed from the equation and it works well when there are lots of useful variables that need to be retained. And it does better than either one when it comes to handling correlated variables. [StatQuest
