# Model Menu for Radiant: Business Analytics using R and Shiny

## Documentation for package ‘radiant.model’ version 1.3.15

- DESCRIPTION file.

## Help Pages

A C D E F G H I K L M N O P R S T V W

## -- A --

ann | Deprecated function(s) in the radiant.model package
auc | Area Under the Curve (AUC)

## -- C --

catalog | Catalog sales for men's and women's apparel
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
cv.rforest | Cross-validation for a Random Forest

## -- D --

direct_marketing | Direct marketing data
dtree | Create a decision tree
dtree_parser | Parse yaml input for dtree to provide (more) useful error messages
dvd | Data on DVD sales

## -- E --

evalbin | Evaluate the performance of different (binary) classification models
evalreg | Evaluate the performance of different regression models

## -- F --

find_max | Find maximum value of a vector
find_min | Find minimum value of a vector

## -- G --

gbt | Gradient Boosted Trees using XGBoost

## -- H --

houseprices | Houseprices

## -- I --

ideal | Ideal data for linear regression

## -- K --

ketchup | Data on ketchup choices

## -- L --

logistic | Logistic regression

## -- M --

MAE | Mean Absolute Error
minmax | Calculate min and max before standardization
mnl | Multinomial logistic regression
movie_contract | Movie contract decision tree

## -- N --

nb | Naive Bayes using e1071::naiveBayes
nn | Neural Networks using nnet

## -- O --

onehot | One hot encoding of data.frames

## -- P --

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.evalbin | Plot method for the evalbin function
plot.evalreg | Plot method for the evalreg function
plot.gbt | Plot method for the gbt function
plot.logistic | Plot method for the logistic function
plot.mnl | Plot method for the mnl function
plot.mnl.predict | Plot method for mnl.predict function
plot.model.predict | Plot method for model.predict functions
plot.nb | Plot method for the nb function
plot.nb.predict | Plot method for nb.predict function
plot.nn | Plot method for the nn function
plot.regress | Plot method for the regress function
plot.repeater | Plot repeated simulation
plot.rforest | Plot method for the rforest function
plot.rforest.predict | Plot method for rforest.predict function
plot.simulater | Plot method for the simulater function
predict.crtree | Predict method for the crtree function
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
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
print.mnl.predict | Print method for mnl.predict
print.nb.predict | Print method for predict.nb
print.nn.predict | Print method for predict.nn
print.regress.predict | Print method for predict.regress
print.rforest.predict | Print method for predict.rforest
print_predict_model | Print method for the model prediction
profit | Calculate Profit based on cost:margin ratio

## -- R --

radiant.model | radiant.model
radiant.model-deprecated | Deprecated function(s) in the radiant.model package
radiant.model_viewer | Launch radiant.model in the Rstudio viewer
radiant.model_window | Launch radiant.model in an Rstudio window
ratings | Movie ratings
regress | Linear regression using OLS
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

## -- S --

scale_df | Center or standardize variables in a data frame
sdw | Standard deviation of weighted sum of variables
sensitivity | Method to evaluate sensitivity of an analysis
sensitivity.dtree | Evaluate sensitivity of the decision tree
simulater | Simulate data for decision 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
store.crs | Deprecated: Store method for the crs function
store.mnl.predict | Store predicted values generated in the mnl function
store.model | Store residuals from a model
store.model.predict | Store predicted values generated in model functions
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.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

## -- T --

test_specs | Add interaction terms to list of test variables if needed

## -- V --

var_check | Check if main effects for all interaction effects are included in the model

## -- W --

write.coeff | Write coefficient table for linear and logistic regression