Model Menu for Radiant: Business Analytics using R and Shiny
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Documentation for package ‘radiant.model’ version 1.6.6
Help Pages
A C D E F G H I K L M N O P R S T U V W misc
-- A --
| ann | Deprecated function(s) in the radiant.model package |
| auc | Area Under the RO 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 --
| kaggle_uplift | Kaggle uplift |
| 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 --
| 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.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 |
| plot.uplift | Plot method for the uplift 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 |
| pred_plot | Prediction Plots |
| 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 |
| 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 |
-- 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 |
| summary.uplift | Summary method for the uplift function |
-- T --
| test_specs | Add interaction terms to list of test variables if needed |
-- U --
| uplift | Evaluate uplift for different (binary) classification models |
-- V --
| varimp | Variable importance using the vip package and permutation importance |
| varimp_plot | Plot permutation importance |
| 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 |
-- misc --
| .as_int | Convenience function used in "simulater" |
| .as_num | Convenience function used in "simulater" |