Package: pre 1.0.7

Marjolein Fokkema

pre: Prediction Rule Ensembles

Derives prediction rule ensembles (PREs). Largely follows the procedure for deriving PREs as described in Friedman & Popescu (2008; <doi:10.1214/07-AOAS148>), with adjustments and improvements. The main function pre() derives prediction rule ensembles consisting of rules and/or linear terms for continuous, binary, count, multinomial, and multivariate continuous responses. Function gpe() derives generalized prediction ensembles, consisting of rules, hinge and linear functions of the predictor variables.

Authors:Marjolein Fokkema [aut, cre], Benjamin Christoffersen [aut]

pre_1.0.7.tar.gz
pre_1.0.7.zip(r-4.5)pre_1.0.7.zip(r-4.4)pre_1.0.7.zip(r-4.3)
pre_1.0.7.tgz(r-4.4-any)pre_1.0.7.tgz(r-4.3-any)
pre_1.0.7.tar.gz(r-4.5-noble)pre_1.0.7.tar.gz(r-4.4-noble)
pre_1.0.7.tgz(r-4.4-emscripten)pre_1.0.7.tgz(r-4.3-emscripten)
pre.pdf |pre.html✨
pre/json (API)
NEWS

# Install 'pre' in R:
install.packages('pre', repos = c('https://marjoleinf.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/marjoleinf/pre/issues

Datasets:
  • carrillo - Data on personality characteristics and depressive symptom severity

On CRAN:

9.15 score 58 stars 1 packages 98 scripts 1.2k downloads 3 mentions 25 exports 28 dependencies

Last updated 5 months agofrom:cc16758b3c. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winNOTENov 17 2024
R-4.5-linuxNOTENov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

Exports:bsnullinteractcaret_pre_modelcorplotcvpreeTermexplaingpegpe_cv.glmnetgpe_earthgpe_lineargpe_rules_pregpe_samplegpe_treesimportanceinteractlTermmaxdepth_samplermi_meanmi_prepairplotpreprune_prerare_level_samplerrTermsingleplot

Dependencies:clicodetoolsearthforeachFormulaglmnetglueinumiteratorslatticelibcoinlifecyclemagrittrMatrixMatrixModelsmvtnormpartykitplotmoplotrixRcppRcppEigenrlangrpartshapestringistringrsurvivalvctrs

Dealing with missing data in fitting prediction rule ensembles

Marjolein Fokkema

Rendered fromMissingness.Rmdusingknitr::rmarkdownon Nov 17 2024.

Last update: 2024-06-20
Started: 2022-02-24

Speeding up computations

Marjolein Fokkema

Rendered fromspeed.Rmdusingknitr::rmarkdownon Nov 17 2024.

Last update: 2024-06-20
Started: 2024-01-12

More adaptive or relaxed: Fitting sparser rule ensembles with relaxed and/or adaptive lasso

Marjolein Fokkema

Rendered fromrelaxed.Rmdusingknitr::rmarkdownon Nov 17 2024.

Last update: 2024-06-20
Started: 2022-03-15

Tuning the parameters of function pre

Marjolein Fokkema

Rendered fromTuning.Rmdusingknitr::rmarkdownon Nov 17 2024.

Last update: 2024-06-20
Started: 2022-02-24

Readme and manuals

Help Manual

Help pageTopics
Compute bootstrapped null interaction prediction rule ensemblesbsnullinteract
Model set up for train function of package caretcaret_pre_model
Data on personality characteristics and depressive symptom severitycarrillo
Coefficients for a General Prediction Ensemble (gpe)coef.gpe
Coefficients for the final prediction rule ensemblecoef.pre
Plot correlations between baselearners in a prediction rule ensemble (pre)corplot
Full k-fold cross validation of a prediction rule ensemble (pre)cvpre
Explain predictions from final prediction rule ensembleexplain
Derive a General Prediction Ensemble (gpe)gpe
Default penalized trainer for gpegpe_cv.glmnet
Get rule learner for gpe which mimics behavior of pregpe_rules_pre
Sampling Function Generator for gpegpe_sample
Learner Functions Generators for gpegpe_earth gpe_linear gpe_trees
Calculate importances of baselearners and input variables in a prediction rule ensemble (pre)importance importance.pre
Calculate interaction statistics for variables in a prediction rule ensemble (pre)interact
Sampling function generator for specifying varying maximum tree depth in a prediction rule ensemble (pre)maxdepth_sampler
Compute the average dataset over imputed datasets.mi_mean
Fit a prediction rule ensemble to multiply-imputed data (experimental)mi_pre
Create partial dependence plot for a pair of predictor variables in a prediction rule ensemble (pre)pairplot
Plot method for class preplot.pre
Derive a prediction rule ensemblepre
Predicted values based on gpe ensemblepredict.gpe
Predicted values based on final prediction rule ensemblepredict.pre
Print a General Prediction Ensemble (gpe)print.gpe
Print method for objects of class preprint.pre
Get the optimal lambda and gamma parameter values for an ensemble of given sizeprune_pre
Dealing with rare factor levels in fitting prediction rule ensembles.rare_level_sampler
Wrapper Functions for terms in gpeeTerm lTerm rTerm
Create partial dependence plot for a single variable in a prediction rule ensemble (pre)singleplot
Summary method for a General Prediction Ensemble (gpe)summary.gpe
Summary method for objects of class presummary.pre