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Create robust models
Regression models two ways
Create and train different kinds of regression models with different computational engines. Read article »
  rsample, parsnip
Classification models using a neural network
Train a classification model and evaluate its performance. Read article »
  rsample, parsnip
Subsampling for class imbalances
Improve model performance in imbalanced data sets through undersampling or oversampling. Read article »
  recipes, themis, discrim, parsnip
Modeling time series with tidy resampling
Calculate performance estimates for time series forecasts using resampling. Read article »
  rsample
Working with model coefficients
Create models that use coefficients, extract them from fitted models, and visualize them. Read article »
  parsnip, tune, broom, workflows
Multivariate analysis using partial least squares
Build and fit a predictive model with more than one outcome. Read article »
  recipes, rsample
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