Model Menu for Radiant: Business Analytics using R and Shiny

auc | Area Under the Curve (AUC) |

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... |

cv.crtree | Cross-validation for Classification and Regression Trees |

cv.nn | Cross-validation for Neural Network |

direct_marketing | Direct marketing data |

dtree | Create a decision tree |

dtree_parser | Parse yaml input for dtree to provide (more) useful error... |

dvd | Data on DVD sales |

evalbin | Evaluate the performance of different (binary) classification... |

evalreg | Evaluate the performance of different regression models |

find_max | Find maximum value of a vector |

find_min | Find minimum value of a vector |

houseprices | Houseprices |

ideal | Ideal data for linear regression |

logistic | Logistic regression |

MAE | Mean Absolute Error |

minmax | Calculate min and max before standardization |

movie_contract | Movie contract decision tree |

nb | Naive Bayes using e1071::naiveBayes |

nn | Neural Networks |

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.logistic | Plot method for the logistic 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.simulater | Plot method for the simulater function |

predict.crtree | Predict method for the crtree function |

predict.logistic | Predict method for the logistic function |

predict_model | Predict method for model functions |

predict.nb | Predict method for the nb function |

predict.nn | Predict method for the nn function |

predict.regress | Predict method for the regress function |

print.crtree.predict | Print method for predict.crtree |

print.logistic.predict | Print method for logistic.predict |

print.nb.predict | Print method for predict.nb |

print.nn.predict | Print method for predict.nn |

print_predict_model | Print method for the model prediction |

print.regress.predict | Print method for predict.regress |

profit | Calculate Profit based on cost:margin ratio |

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 |

RMSE | Root Mean Squared Error |

Rsq | R-squared |

scaledf | 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 |

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.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 |

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.logistic | Summary method for the logistic 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.simulater | Summary method for the simulater function |

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

var_check | Check if main effects for all interaction effects are... |

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

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