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regressoR (version 3.0.2)

Regression Data Analysis System

Description

Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.

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Version

Install

install.packages('regressoR')

Monthly Downloads

540

Version

3.0.2

License

GPL (>= 2)

Issues

Pull Requests

Stars

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Maintainer

Oldemar Rodriguez

Last Published

June 29th, 2023

Functions in regressoR (3.0.2)

rlr_prediction

rlr_prediction
rd_prediction

rd_prediction
rlr_type

rlr_type
exe

exe
rd_type

rd_type
rl_coeff

rl_coeff
rlr_model

rlr_model
dt_plot

dt_plot
disp_models

disp_models
coef_lambda

coef_lambda
e_coeff_landa

e_coeff_landa
boosting_importance_plot

boosting_importance_plot
e_JS

Eval character vectors to JS code
as_string_c

as_string_c
datos.disyuntivos

Create disjunctive columns to a data.frame.
app_server

The application server-side
calibrate_boosting

calibrate_boosting
plot_pred_rd

plot_pred_rd
extract_code

extract_code
pairs_power

pairs_power
e_posib_lambda

e_posib_lambda
importance_plot_rf

importance_plot_rf
nn_plot

nn_plot
run_app

Run the Shiny Application
plot_real_prediction

plot_real_prediction
rd_model

rd_model
plot_var_pred_rd

plot_var_pred_rd
plot_RMSE

plot_RMSE
general_indices

general_indices
summary_indices

summary_indices