Automatic Machine Learning with 'tidymodels'
Check for Duplicate Rows in a Data Frame
Functions to Install all Core Libraries
Generate Model Specification calls to parsnip
Utility Create Splits Object
Create a Workflow Set Object
Extract A Model Specification
Extract Residuals from Fast Regression Models
Extract Tunable Parameters from Model Specifications
Extract A Model Fitted Workflow
Extract A Model Workflow Predictions
Extract A Model Workflow
Utility Classification call to parsnip
Generate Model Specification calls to parsnip
Utility Regression call to parsnip
Generate Model Specification calls to parsnip
Full Internal Workflow for Model and Recipe
Get a Model
Functions to Install all Core Libraries
Internals Safely Make a Fitted Workflow from Model Spec tibble
Internals Make a Model Spec tibble
Internals Safely Make Workflow for GEE Linear Regression
Internals Safely Make Predictions on a Fitted Workflow from Model Spec...
Internals Safely Make Workflow from Model Spec tibble
Internals Make a Tunable Model Specification
Functions to Install all Core Libraries
Internals Make Base Classification Tibble
Internals Make Base Regression Tibble
Match function arguments
Pipe operator
Create ggplot2 plot of regression predictions
Create ggplot2 plot of regression residuals
Perform quantile normalization on a numeric matrix/data.frame
Tidy eval helpers
The goal of this package will be to provide a simple interface for automatic machine learning that fits the 'tidymodels' framework. The intention is to work for regression and classification problems with a simple verb framework.
Useful links