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regressoR (version 2.0.1)

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

2.0.1

License

GPL (>= 2)

Maintainer

Oldemar Rodriguez

Last Published

October 13th, 2021

Functions in regressoR (2.0.1)

e_histboxplot

Histogram + boxplot
e_boxplot

Generate horizontal boxplot
nn_plot

nn_plot
e_JS

Eval character vectors to JS code
nn_model

nn_model
mod_carga_datos_server

carga_datos Server Function
listoutliers

List outliers
dt_prediction

dt_prediction
disp_models

disp_models
dt_plot

dt_plot
coef_lambda

coef_lambda
exe

exe
dt_model

dt_model
e_histnormal

Normal plot
e_cor

Correlation plot
mod_correlacion_server

correlacion Server Function
e_coeff_landa

e_coeff_landa
e_qq

Qplot + Qline
e_posib_lambda

e_posib_lambda
mod_dispersion_server

dispersion Server Function
rf_prediction

rf_prediction
mod_normal_server

normal Server Function
rl_coeff

rl_coeff
kkn_model

kkn_model
summary_indices

summary_indices
rlr_model

rlr_model
rlr_prediction

rlr_prediction
svm_model

svm_model
rd_type

rd_type
extract_code

extract_code
rf_model

rf_model
general_indices

general_indices
importance_plot_rf

importance_plot_rf
rlr_type

rlr_type
run_app

Run the Shiny Application
plot_real_prediction

plot_real_prediction
mod_distribuciones_server

distribuciones Server Function
plot_var_pred_rd

plot_var_pred_rd
rd_model

rd_model
nn_prediction

nn_prediction
kkn_prediction

kkn_prediction
mod_new_data_predictions_server

new_data_predictions Server Function
rd_prediction

rd_prediction
svm_prediction

svm_prediction
mod_r_numerico_server

r_numerico Server Function
translate

translate
plot_RMSE

plot_RMSE
pairs_power

pairs_power
plot_pred_rd

plot_pred_rd
rl_prediction

rl_prediction
rl_model

rl_model
boosting_prediction

boosting_prediction
boosting_model

boosting_model
datos.disyuntivos

Create disjunctive columns to a data.frame.
as_string_c

as_string_c
boosting_importance_plot

boosting_importance_plot
calibrate_boosting

calibrate_boosting
dfnormal

Data.frame with normal test
addoutliersh

Add outliers Horizontal
app_server

The application server-side