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Tune, compare, and work with your models
Model tuning via grid search
Choose hyperparameters for a model by training on a grid of many possible parameter values. Read article »
  rsample, parsnip, tune, yardstick
Nested resampling
Estimate the best hyperparameters for a model using nested resampling. Read article »
  rsample, parsnip
Iterative Bayesian optimization of a classification model
Identify the best hyperparameters for a model using Bayesian optimization of iterative search. Read article »
  tune, dials, parsnip, recipes, workflows
Tuning text models
Prepare text data for predictive modeling and tune with both grid and iterative search. Read article »
  rsample, recipes, textrecipes, parsnip, tune, yardstick
Creating case weights based on time
Create models that use coefficients, extract them from fitted models, and visualize them. Read article »
  parsnip, tune, recipes, workflows
Multi-scale model assessment with spatialsample
Assess how accurate a model is when aggregating predictions to different spatial scales. Read article »
  spatialsample, rsample, parsnip
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