radiant.model1.6.7 package

Model Menu for Radiant: Business Analytics using R and Shiny

profit

Calculate Profit based on cost:margin ratio

radiant.model-deprecated

Deprecated function(s) in the radiant.model package

radiant.model

radiant.model

radiant.model_viewer

Launch radiant.model in the Rstudio viewer

radiant.model_window

Launch radiant.model in an Rstudio window

store.model.predict

Store predicted values generated in model functions

store.model

Store residuals from a model

store.nb.predict

Store predicted values generated in the nb function

store.rforest.predict

Store predicted values generated in the rforest function

summary.confusion

Summary method for the confusion matrix

summary.crs

Summary method for Collaborative Filter

summary.crtree

Summary method for the crtree function

summary.dtree

Summary method for the dtree function

summary.evalbin

Summary method for the evalbin function

summary.evalreg

Summary method for the evalreg function

summary.gbt

Summary method for the gbt function

summary.uplift

Summary method for the uplift function

test_specs

Add interaction terms to list of test variables if needed

print_predict_model

Print method for the model prediction

sdw

Standard deviation of weighted sum of variables

find_min

Find minimum value of a vector

auc

Area Under the RO Curve (AUC)

confint_robust

Confidence interval for robust estimators

confusion

Confusion matrix

crs

Collaborative Filtering

crtree

Classification and regression trees based on the rpart package

cv.crtree

Cross-validation for Classification and Regression Trees

cv.gbt

Cross-validation for Gradient Boosted Trees

cv.nn

Cross-validation for a Neural Network

plot.evalreg

Plot method for the evalreg function

cv.rforest

Cross-validation for a Random Forest

dot-as_int

Convenience function used in "simulater"

dot-as_num

Convenience function used in "simulater"

dtree

Create a decision tree

dtree_parser

Parse yaml input for dtree to provide (more) useful error messages

evalbin

Evaluate the performance of different (binary) classification models

evalreg

Evaluate the performance of different regression models

find_max

Find maximum value of a vector

gbt

Gradient Boosted Trees using XGBoost

logistic

Logistic regression

MAE

Mean Absolute Error

minmax

Calculate min and max before standardization

mnl

Multinomial logistic regression

nb

Naive Bayes using e1071::naiveBayes

plot.evalbin

Plot method for the evalbin function

nn

Neural Networks using nnet

onehot

One hot encoding of data.frames

pdp_plot

Create Partial Dependence Plots

plot.confusion

Plot method for the confusion matrix

plot.crs

Plot method for the crs function

plot.crtree

Plot method for the crtree function

plot.dtree

Plot method for the dtree function

plot.gbt

Plot method for the gbt function

plot.logistic

Plot method for the logistic function

plot.mnl.predict

Plot method for mnl.predict function

plot.mnl

Plot method for the mnl function

plot.model.predict

Plot method for model.predict functions

print.mnl.predict

Print method for mnl.predict

plot.nb.predict

Plot method for nb.predict function

plot.nb

Plot method for the nb function

plot.nn

Plot method for the nn function

plot.regress

Plot method for the regress function

plot.repeater

Plot repeated simulation

plot.rforest.predict

Plot method for rforest.predict function

plot.rforest

Plot method for the rforest function

plot.simulater

Plot method for the simulater function

plot.uplift

Plot method for the uplift function

pred_plot

Prediction Plots

predict.crtree

Predict method for the crtree function

print.nb.predict

Print method for predict.nb

print.nn.predict

Print method for predict.nn

predict.gbt

Predict method for the gbt function

predict.logistic

Predict method for the logistic function

predict.mnl

Predict method for the mnl function

predict.nb

Predict method for the nb function

print.regress.predict

Print method for predict.regress

print.rforest.predict

Print method for predict.rforest

predict.nn

Predict method for the nn function

predict.regress

Predict method for the regress function

predict.rforest

Predict method for the rforest function

predict_model

Predict method for model functions

print.crtree.predict

Print method for predict.crtree

print.gbt.predict

Print method for predict.gbt

print.logistic.predict

Print method for logistic.predict

regress

Linear regression using OLS

remove_comments

Remove comments from formula before it is evaluated

render.DiagrammeR

Method to render DiagrammeR plots

repeater

Repeated simulation

rforest

Random Forest using Ranger

rig

Relative Information Gain (RIG)

RMSE

Root Mean Squared Error

Rsq

R-squared

scale_df

Center or standardize variables in a data frame

sensitivity.dtree

Evaluate sensitivity of the decision tree

sensitivity

Method to evaluate sensitivity of an analysis

sim_cleaner

Clean input command string

sim_cor

Simulate correlated normally distributed data

sim_splitter

Split input command string

sim_summary

Print simulation summary

simulater

Simulate data for decision analysis

store.crs

Deprecated: Store method for the crs function

store.mnl.predict

Store predicted values generated in the mnl function

summary.logistic

Summary method for the logistic function

summary.mnl

Summary method for the mnl function

summary.nb

Summary method for the nb function

summary.nn

Summary method for the nn function

summary.regress

Summary method for the regress function

summary.repeater

Summarize repeated simulation

summary.rforest

Summary method for the rforest function

summary.simulater

Summary method for the simulater function

uplift

Evaluate uplift for different (binary) classification models

var_check

Check if main effects for all interaction effects are included in the ...

varimp

Variable importance using the vip package and permutation importance

varimp_plot

Plot permutation importance

write.coeff

Write coefficient table for linear and logistic regression

The Radiant Model menu includes interfaces for linear and logistic regression, naive Bayes, neural networks, classification and regression trees, model evaluation, collaborative filtering, decision analysis, and simulation. The application extends the functionality in 'radiant.data'.

  • Maintainer: Vincent Nijs
  • License: AGPL-3 | file LICENSE
  • Last published: 2024-10-11