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rsample
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
Regression models two ways
Create and train different kinds of regression models with different computational engines. Read more »
  rsample, parsnip
Classification models using a neural network
Train a classification model and evaluate its performance. Read more »
  rsample, parsnip
Nested resampling
Estimate the best hyperparameters for a model using nested resampling. Read more »
  rsample, parsnip
Bootstrap resampling and tidy regression models
Apply bootstrap resampling to estimate uncertainty in model parameters. Read more »
  rsample, broom
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
Modeling time series with tidy resampling
Calculate performance estimates for time series forecasts using resampling. Read more »
  rsample
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
Multi-scale model assessment with spatialsample
Assess how accurate a model is when aggregating predictions to different spatial scales. Read more »
  spatialsample, rsample, parsnip
Multivariate analysis using partial least squares
Build and fit a predictive model with more than one outcome. Read more »
  recipes, rsample
Resources
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