Package: radiant.model 1.6.7

Vincent Nijs

radiant.model: Model Menu for Radiant: Business Analytics using R and Shiny

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'.

Authors:Vincent Nijs [aut, cre]

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radiant.model.pdf |radiant.model.html✨
radiant.model/json (API)
NEWS

# Install 'radiant.model' in R:

install.packages('radiant.model', repos = c('https://radiant-rstats.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/radiant-rstats/radiant.model/issues

Pkgdown site:https://radiant-rstats.github.io

Datasets:

catalog - Catalog sales for men's and women's apparel
direct_marketing - Direct marketing data
dvd - Data on DVD sales
houseprices - Houseprices
ideal - Ideal data for linear regression
kaggle_uplift - Kaggle uplift
ketchup - Data on ketchup choices
movie_contract - Movie contract decision tree
ratings - Movie ratings

On CRAN:

6.16 score 20 stars 2 packages 80 scripts 933 downloads 1 mentions 55 exports 158 dependencies

Last updated 4 months agofrom:347a11b712. Checks:8 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Feb 08 2025
R-4.5-win	OK	Feb 08 2025
R-4.5-mac	OK	Feb 08 2025
R-4.5-linux	OK	Feb 08 2025
R-4.4-win	OK	Feb 08 2025
R-4.4-mac	OK	Feb 08 2025
R-4.3-win	OK	Feb 08 2025
R-4.3-mac	OK	Feb 08 2025

Exports:.as_int .as_num ann auc confint_robust confusion crs crtree cv.crtree cv.gbt cv.nn cv.rforest dtree dtree_parser evalbin evalreg find_max find_min gbt logistic MAE minmax mnl nb nn onehot pdp_plot pred_plot predict_model print_predict_model profit radiant.model radiant.model_viewer radiant.model_window regress remove_comments repeater rforest rig RMSE Rsq scale_df sdw sensitivity sim_cleaner sim_cor sim_splitter sim_summary simulater test_specs uplift var_check varimp varimp_plot write.coeff

Dependencies:abind admisc askpass backports base64enc bit bit64 boot broom bslib cachem car carData cellranger class cli clipr codetools colorspace commonmark cowplot cpp11 crayon crosstalk curl data.table data.tree Deriv DiagrammeR digest doBy dplyr DT e1071 evaluate fansi farver fastmap fontawesome foreach Formula fs generics ggplot2 ggrepel glue GPArotation gtable hardhat highr hms htmltools htmlwidgets httpuv httr igraph import isoband iterators jquerylib jsonlite knitr labeling later lattice lazyeval lifecycle lme4 lubridate magrittr markdown MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa mnormt modelr munsell mvtnorm NeuralNetTools nlme nloptr nnet numDeriv openssl patchwork pbkrtest pdp pillar pkgconfig plotly plyr png polycor prettyunits progress promises proxy psych purrr quantreg R6 radiant.basics radiant.data randomizr ranger rappdirs rbibutils RColorBrewer Rcpp RcppEigen Rdpack readr readxl reformulas rematch reshape2 rlang rmarkdown rpart rstudioapi sandwich sass scales shiny shinyAce shinyFiles sourcetools SparseM sparsevctrs stringi stringr survival sys tibble tidyr tidyselect timechange tinytex tzdb utf8 vctrs vip viridisLite visNetwork vroom withr writexl xfun xgboost xtable yaml yardstick zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Convenience function used in "simulater"	.as_int
Convenience function used in "simulater"	.as_num
Area Under the RO Curve (AUC)	auc
Catalog sales for men's and women's apparel	catalog
Confidence interval for robust estimators	confint_robust
Confusion matrix	confusion
Collaborative Filtering	crs
Classification and regression trees based on the rpart package	crtree
Cross-validation for Classification and Regression Trees	cv.crtree
Cross-validation for Gradient Boosted Trees	cv.gbt
Cross-validation for a Neural Network	cv.nn
Cross-validation for a Random Forest	cv.rforest
Direct marketing data	direct_marketing
Create a decision tree	dtree
Parse yaml input for dtree to provide (more) useful error messages	dtree_parser
Data on DVD sales	dvd
Evaluate the performance of different (binary) classification models	evalbin
Evaluate the performance of different regression models	evalreg
Find maximum value of a vector	find_max
Find minimum value of a vector	find_min
Gradient Boosted Trees using XGBoost	gbt
Houseprices	houseprices
Ideal data for linear regression	ideal
Kaggle uplift	kaggle_uplift
Data on ketchup choices	ketchup
Logistic regression	logistic
Mean Absolute Error	MAE
Calculate min and max before standardization	minmax
Multinomial logistic regression	mnl
Movie contract decision tree	movie_contract
Naive Bayes using e1071::naiveBayes	nb
Neural Networks using nnet	nn
One hot encoding of data.frames	onehot
Create Partial Dependence Plots	pdp_plot
Plot method for the confusion matrix	plot.confusion
Plot method for the crs function	plot.crs
Plot method for the crtree function	plot.crtree
Plot method for the dtree function	plot.dtree
Plot method for the evalbin function	plot.evalbin
Plot method for the evalreg function	plot.evalreg
Plot method for the gbt function	plot.gbt
Plot method for the logistic function	plot.logistic
Plot method for the mnl function	plot.mnl
Plot method for mnl.predict function	plot.mnl.predict
Plot method for model.predict functions	plot.model.predict
Plot method for the nb function	plot.nb
Plot method for nb.predict function	plot.nb.predict
Plot method for the nn function	plot.nn
Plot method for the regress function	plot.regress
Plot repeated simulation	plot.repeater
Plot method for the rforest function	plot.rforest
Plot method for rforest.predict function	plot.rforest.predict
Plot method for the simulater function	plot.simulater
Plot method for the uplift function	plot.uplift
Prediction Plots	pred_plot
Predict method for model functions	predict_model
Predict method for the crtree function	predict.crtree
Predict method for the gbt function	predict.gbt
Predict method for the logistic function	predict.logistic
Predict method for the mnl function	predict.mnl
Predict method for the nb function	predict.nb
Predict method for the nn function	predict.nn
Predict method for the regress function	predict.regress
Predict method for the rforest function	predict.rforest
Print method for the model prediction	print_predict_model
Print method for predict.crtree	print.crtree.predict
Print method for predict.gbt	print.gbt.predict
Print method for logistic.predict	print.logistic.predict
Print method for mnl.predict	print.mnl.predict
Print method for predict.nb	print.nb.predict
Print method for predict.nn	print.nn.predict
Print method for predict.regress	print.regress.predict
Print method for predict.rforest	print.rforest.predict
Calculate Profit based on cost:margin ratio	profit
radiant.model	radiant.model
Launch radiant.model in the Rstudio viewer	radiant.model_viewer
Launch radiant.model in an Rstudio window	radiant.model_window
Deprecated function(s) in the radiant.model package	ann radiant.model-deprecated
Movie ratings	ratings
Linear regression using OLS	regress
Remove comments from formula before it is evaluated	remove_comments
Method to render DiagrammeR plots	render.DiagrammeR
Repeated simulation	repeater
Random Forest using Ranger	rforest
Relative Information Gain (RIG)	rig
Root Mean Squared Error	RMSE
R-squared	Rsq
Center or standardize variables in a data frame	scale_df
Standard deviation of weighted sum of variables	sdw
Method to evaluate sensitivity of an analysis	sensitivity
Evaluate sensitivity of the decision tree	sensitivity.dtree
Clean input command string	sim_cleaner
Simulate correlated normally distributed data	sim_cor
Split input command string	sim_splitter
Print simulation summary	sim_summary
Simulate data for decision analysis	simulater
Deprecated: Store method for the crs function	store.crs
Store predicted values generated in the mnl function	store.mnl.predict
Store residuals from a model	store.model
Store predicted values generated in model functions	store.model.predict
Store predicted values generated in the nb function	store.nb.predict
Store predicted values generated in the rforest function	store.rforest.predict
Summary method for the confusion matrix	summary.confusion
Summary method for Collaborative Filter	summary.crs
Summary method for the crtree function	summary.crtree
Summary method for the dtree function	summary.dtree
Summary method for the evalbin function	summary.evalbin
Summary method for the evalreg function	summary.evalreg
Summary method for the gbt function	summary.gbt
Summary method for the logistic function	summary.logistic
Summary method for the mnl function	summary.mnl
Summary method for the nb function	summary.nb
Summary method for the nn function	summary.nn
Summary method for the regress function	summary.regress
Summarize repeated simulation	summary.repeater
Summary method for the rforest function	summary.rforest
Summary method for the simulater function	summary.simulater
Summary method for the uplift function	summary.uplift
Add interaction terms to list of test variables if needed	test_specs
Evaluate uplift for different (binary) classification models	uplift
Check if main effects for all interaction effects are included in the model	var_check
Variable importance using the vip package and permutation importance	varimp
Plot permutation importance	varimp_plot
Write coefficient table for linear and logistic regression	write.coeff