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parsnip
Build a model
Get started by learning how to specify and train a model using tidymodels. Read more »
  parsnip, broom
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
How to build a parsnip model
Create a parsnip model function from an existing model implementation. Read more »
  parsnip
Nested resampling
Estimate the best hyperparameters for a model using nested resampling. Read more »
  rsample, parsnip
Preprocess your data with recipes
Prepare data for modeling with modular preprocessing steps. Read more »
  recipes, parsnip, workflows, yardstick, 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
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
Subsampling for class imbalances
Improve model performance in imbalanced data sets through undersampling or oversampling. Read more »
  recipes, themis, discrim, parsnip
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
Multi-scale model assessment with spatialsample
Assess how accurate a model is when aggregating predictions to different spatial scales. Read more »
  spatialsample, rsample, parsnip
Working with model coefficients
Create models that use coefficients, extract them from fitted models, and visualize them. Read more »
  parsnip, tune, broom, workflows
Resources
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  News
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