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mlcourse.ai. Assignment #4 (demo)
Exploring OLS, Lasso, Ridge and Random Forest in a regression task
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1. What are mean squared errors of model predictions on train and holdout sets? *
2 points
2. Which feature this linear regression model treats as the most influential on wine quality? *
1 point
3. Which feature is the least informative in predicting wine quality, according to the tuned LASSO model? *
2 points
4.  What are mean squared errors of tuned LASSO predictions on train and holdout sets? *
1 point
5. What are mean squared errors of RF model on the training set, in cross-validation and on holdout set? *
2 points
6. What are mean squared errors of tuned RF model in cross-validation and on holdout set? *
1 point
7. What is the most important feature, according to the Random Forest model? *
1 point
Do you have any remarks concerning the assignment? In case of apparent errors/typos please use GitHub Issues and/or Pull Requests (https://github.com/Yorko/mlcourse.ai).
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