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1
Introduction
2
Getting the data
3
Building the dataset
4
Building the data set
5
Separate rows
6
Putting it all together
7
Show Legend
8
APIs
9
Test split
10
Update Role
11
Workflow
12
Lasso fit
13
Grid function
14
Grid metrics
15
Error bars
16
Visualization
17
Finalisation
18
Final lasso
19
Variable importance
20
Reordering variables
21
Rerendering
22
Testing
23
Conclusion
Description:
Implement lasso regularized regression modeling in R using tidymodels and #TidyTuesday data on episodes of The Office. Explore the process of building a dataset, separating rows, creating a workflow, and performing lasso fit with grid functions. Visualize error bars, analyze variable importance, and reorder variables for optimal results. Test the model and draw conclusions from this practical application of machine learning techniques to analyze popular TV show data.

Lasso Regression with Tidymodels and The Office

Julia Silge
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