R: Build and Tune Several Models

# Build and Tune Several Models

## Documentation for package ‘manymodelr’ version 0.4.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

add_model_predictions | Add predictions to the data set. A dplyr compatible way to add predictions to a data set.
add_model_residuals | Add model residuals
agg_by_group | A convenient way to perform grouped operations
drop_non_numeric | Drops non numeric columns from a data.frame object
extract_model_info | Extract important model attributes
fit_model | Fit and predict in a single function.
fit_models | Fit several models with different response variables
get_data_Stats | A pipe friendly way to get summary stats for exploratory data analysis
get_exponent | Get the exponent of any number or numbers
get_mode | A convenience function that returns the mode
get_stats | A pipe friendly way to get summary stats for exploratory data analysis
get_this | Helper function to easily access elements
get_var_corr | Get correlations between variables
get_var_corr_ | Get correlations for combinations
multi_model_1 | Simultaneously train and predict on new data.
multi_model_2 | Fit and predict in one function
na_replace | Replace missing values
na_replace_grouped | Replace NAs by group
plot_corr | Plot a correlations matrix
report_model | Create a simplified report of a model's summary
rowdiff | Get row differences between values
select_col | A convenient selector gadget
select_percentile | Get the row corresponding to a given percentile
yields | Plant yields