Congratulations!

Modeling with tidymodels in R

David Svancer

Data Scientist

The tidymodels ecosystem

Regression modeling

Specifying models with parsnip

 

Training and evaluating linear regression models

Classification modeling

Logistic regression with logistic_reg()

 

Evaluating classification performance with confusion matrices and ROC curves

Feature engineering

Fine tuning models with cross validation

Model performance profiles with cross validation and fit_resamples()

 

• Hyperparameter tuning with grid search
• Finalizing model workflows

 

cost_complexity	tree_depth	min_n
0.001	20	35
0.001	20	15
0.001	35	35
0.001	35	15
0.2	20	35
...	...	...

Thank you!

Modeling with tidymodels in R