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manymodelr (version 0.3.9)

Build and Tune Several Models

Description

Frequently one needs a convenient way to build and tune several models in one go.The goal is to provide a number of machine learning convenience functions. It provides the ability to build, tune and obtain predictions of several models in one function. The models are built using functions from 'caret' with easier to read syntax. Kuhn(2014) .

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Install

install.packages('manymodelr')

Monthly Downloads

336

Version

0.3.9

License

GPL-2

Issues

6

Pull Requests

0

Stars

2

Forks

3

Maintainer

Nelson Gonzabato

Last Published

March 20th, 2025

Functions in manymodelr (0.3.9)

na_replace

Replace missing values
report_model

Create a simplified report of a model's summary
multi_model_1

Simultaneously train and predict on new data.
get_var_corr

Get correlations between variables
rowdiff

Get row differences between values
yields

Plant yields
plot_corr

Plot a correlations matrix
select_percentile

Get the row corresponding to a given percentile
select_col

A convenient selector gadget
drop_non_numeric

Drops non numeric columns from a data.frame object
fit_model

Fit and predict in a single function.
fit_models

Fit several models with different response variables
agg_by_group

A convenient way to perform grouped operations
get_data_Stats

A pipe friendly way to get summary stats for exploratory data analysis
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
extract_model_info

Extract important model attributes
get_exponent

Get the exponent of any number or numbers
get_mode

A convenience function that returns the mode
multi_model_2

Fit and predict in one function
get_var_corr_

Get correlations for combinations
get_this

Helper function to easily access elements
na_replace_grouped

Replace NAs by group