dot-extract_bagger_classprob: Extract class probability trees for bagger models
In tidypredict: Run Predictions Inside the Database

.extract_bagger_classprob

R Documentation

Extract class probability trees for bagger models

Description

Returns one list of per-tree expressions for each outcome level. For use in orbital package.

Usage

.extract_bagger_classprob(model)

Arguments

model

A bagger model object (classification)

tidypredict documentation built on Oct. 18, 2026, 5:06 p.m.

tidypredict index

Package overview README.md bagger models bart models Create a regression spec - version 2 Create a tree spec - version 2 Cubist models Database write-back Decision trees, using C5.0 Decision trees, using rpart fda models Float precision at split boundaries Generalized Linear Regression glmnet models Gradient boosting, using H2O How tidypredict generates tree formulas lda models LightGBM models Linear Regression MARS models via the `earth` package mixOmics PLS models Model-based boosting, using mboost multinom models NaiveBayes models nnet models Non-R Models nullmodel models Oblique Random Forest, using aorsf qda models Random Forest Random Forest - partykit Random Forest, using Ranger RuleFit, using xrf Save and re-load models sda models sparsediscrim models Supported models Support vector machines, using kernlab XGBoost models

rdrr.io home R language documentation Run R code online

CRAN packages Bioconductor packages R-Forge packages GitHub packages

Note that we can't provide technical support on individual packages. You should contact the package authors for that.

Tweet to @rdrrHQ

GitHub issue tracker

ian@mutexlabs.com