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regressoR

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.

Installation

We are working to upload the package to CRAN, at the moment the available version is the development version from GitHub.

# install.packages("devtools")
devtools::install_github("promidat/regressor")

Start regressoR

library(regressoR)
init_regressor()

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Version

Install

install.packages('regressoR')

Monthly Downloads

540

Version

1.2.1

License

GPL (>= 2)

Maintainer

Oldemar Rodriguez

Last Published

April 6th, 2021

Functions in regressoR (1.2.1)

colnames_empty

colnames_empty
extract_code

extract_code
disjunctive_data

disjunctive_data
code_deactivate

code_deactivate
infoBoxPROMiDAT

infoBoxPROMiDAT
default_disp

default_disp
exe

exe
dt_plot

dt_plot
chunk

chunk
code_field

code_field
init_regressor

This function will start regressoR
dt_prediction

dt_prediction
coef_lambda

coef_lambda
kkn_prediction

kkn_prediction
general_indices

general_indices
fisher_calc

fisher_calc
code_transf

code_transf
kkn_model

kkn_model
options_regressor

options_regressor
order_report

order_report
comparative_table

comparative_table
plot_RMSE

plot_RMSE
rl_prediction

rl_prediction
error_variables

error_variables
error_plot

error_plot
rf_prediction

rf_prediction
plot_coef_lambda

plot_coef_lambda
rf_model

rf_model
rd_model

rd_model
new_report

new_report
models_mode

models_mode
new_section_report

new_section_report
new_col

new_col
combine_names

combine_names
rd_prediction

rd_prediction
rlr_model

rlr_model
tabsOptions

tabsOptions
svm_prediction

svm_prediction
def_code_num

def_code_num
code_load

code_load
gg_color_hue

gg_color_hue
default_calc_normal

default_calc_normal
disp_models

disp_models
importance_plot_rf

importance_plot_rf
code_summary

code_summary
render_index_table

render_index_table
validate_pn_data

validate_pn_data
render_table_data

render_table_data
cor_model

cor_model
correlations_plot

correlations_plot
def_code_cat

def_code_cat
var_categorical

var_categorical
dt_model

dt_model
get_env_report

get_env_report
get_report

get_report
inputRadio

inputRadio
insert_report

insert_report
nn_prediction

nn_prediction
labelInput

labelInput
plot_var_pred_rd

plot_var_pred_rd
normal_default

normal_default
radioButtonsTr

radioButtonsTr
numerical_distribution

numerical_distribution
numerical_summary

numerical_summary
len_report

len_report
nn_model

nn_model
plot_pred_rd

plot_pred_rd
rl_coeff

rl_coeff
plot_real_prediction

plot_real_prediction
summary_indices

summary_indices
rd_type

rd_type
remove_report_elem

remove_report_elem
nn_plot

nn_plot
rl_model

rl_model
svm_model

svm_model
pairs_power

pairs_power
tb_predic

tb_predic
var_numerical

var_numerical
translate

translate
rlr_prediction

rlr_prediction
rlr_type

rlr_type
partition_code

partition_code
word_report

word_report
clean_report

clean_report
as_string_c

as_string_c
boosting_importance_plot

boosting_importance_plot
categorical_summary

categorical_summary
boosting_model

boosting_model
code_NA

code_NA
boosting_prediction

boosting_prediction
calibrate_boosting

calibrate_boosting
categorical_distribution

categorical_distribution