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bartMachine (version 1.2.3)
Bayesian Additive Regression Trees
Description
An advanced implementation of Bayesian Additive Regression Trees with expanded features for data analysis and visualization.
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Install
install.packages('bartMachine')
Monthly Downloads
2,534
Version
1.2.3
License
GPL-3
Maintainer
Adam Kapelner
Last Published
May 12th, 2016
Functions in bartMachine (1.2.3)
Search functions
bartMachineCV
Build BART-CV
bart_predict_for_test_data
Predict for Test Data with Known Outcomes
benchmark_datasets
benchmark_datasets
dummify_data
Dummify Design Matrix
calc_prediction_intervals
Calculate Prediction Intervals
automobile
Data concerning automobile prices.
var_selection_by_permute
Perform Variable Selection using Three Threshold-based Procedures
plot_convergence_diagnostics
Plot Convergence Diagnostics
calc_credible_intervals
Calculate Credible Intervals
set_bart_machine_num_cores
Set the Number of Cores for BART
var_selection_by_permute_cv
Perform Variable Selection Using Cross-validation Procedure
predict_bartMachineArr
Make a prediction on data using a BART array object
pd_plot
Partial Dependence Plot
predict.bartMachine
Make a prediction on data using a BART object
get_var_counts_over_chain
Get the Variable Inclusion Counts
get_sigsqs
Get Posterior Error Variance Estimates
summary.bartMachine
Summarizes information about a
bartMachine
object.
bartMachineArr
Create an array of BART models for the same data.
interaction_investigator
Explore Pairwise Interactions in BART Model
investigate_var_importance
Explore Variable Inclusion Proportions in BART Model
k_fold_cv
Estimate Out-of-sample Error with K-fold Cross validation
linearity_test
Test of Linearity
bart_machine_num_cores
Get Number of Cores Used by BART
plot_y_vs_yhat
Plot the fitted Versus Actual Response
destroy_bart_machine
Destroy BART Model (deprecated --- do not use!)
check_bart_error_assumptions
Check BART Error Assumptions
print.bartMachine
Summarizes information about a
bartMachine
object.
cov_importance_test
Importance Test for Covariate(s) of Interest
rmse_by_num_trees
Assess the Out-of-sample RMSE by Number of Trees
bart_machine_get_posterior
Get Full Posterior Distribution
get_var_props_over_chain
Get the Variable Inclusion Proportions
bartMachine
Build a BART Model