Build and Tune Several Models


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Documentation for package ‘manymodelr’ version 0.3.7

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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
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