Back to Learn
tune
Model tuning via grid search
Choose hyperparameters for a model by training on a grid of many possible parameter values. Read more »
  rsample, parsnip, tune, yardstick
Evaluate your model with resampling
Measure model performance by generating different versions of the training data through resampling. Read more »
  rsample, parsnip, tune, workflows, yardstick
Iterative Bayesian optimization of a classification model
Identify the best hyperparameters for a model using Bayesian optimization of iterative search. Read more »
  tune, dials, parsnip, recipes, workflows
Tune model parameters
Estimate the best values for hyperparameters that cannot be learned directly during model training. Read more »
  rsample, parsnip, tune, dials, workflows, yardstick
Tuning text models
Prepare text data for predictive modeling and tune with both grid and iterative search. Read more »
  rsample, recipes, textrecipes, parsnip, tune, yardstick
A predictive modeling case study
Develop, from beginning to end, a predictive model using best practices. Read more »
  parsnip, recipes, rsample, workflows, tune
Creating case weights based on time
Create models that use coefficients, extract them from fitted models, and visualize them. Read more »
  parsnip, tune, recipes, workflows
Working with model coefficients
Create models that use coefficients, extract them from fitted models, and visualize them. Read more »
  parsnip, tune, broom, workflows
Resources
  Find
Explore searchable tables of all tidymodels packages and functions.
  Books
Study up on statistics and modeling with our comprehensive books.
  News
Hear the latest about tidymodels packages at the tidyverse blog.