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inTrees (version 1.3)

Interpret Tree Ensembles

Description

For tree ensembles such as random forests, regularized random forests and gradient boosted trees, this package provides functions for: extracting, measuring and pruning rules; selecting a compact rule set; summarizing rules into a learner; calculating frequent variable interactions; formatting rules in latex code. Reference: Interpreting tree ensembles with inTrees (Houtao Deng, 2019, ).

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Version

Install

install.packages('inTrees')

Monthly Downloads

924

Version

1.3

License

GPL (>= 3)

Maintainer

Houtao Deng

Last Published

May 31st, 2022

Functions in inTrees (1.3)

pruneSingleRule

internal
getRuleMetric

Assign outcomes to a conditions, and measure the rules
rule2Table

internal function
getTypeX

get type of each variable
lookupRule

internal
measureRule

internal
XGB2List

Transform an xgboost object to a list of trees
voteAllRules

internal
treeVisit

internal function
formatGBM

internal
presentRules

Present a learner using column names instead of X[i,]
getFreqPattern

calculate frequent variable interactions
pruneRule

Prune irrevant variable-value pair from a rule condition
ruleList2Exec

internal
selectRuleRRF

select a set of relevant and non-redundant rules
sortRule

internal
singleRuleList2Exec

internal
computeRuleInfor

compute rule information
dicretizeVector

discretize a variable
extractRules

Extract rules from a list of trees
Num2Level

internal function
GBM2List

Transform gbm object to a list of trees
dataSimulate

Simulate data
RF2List

Transform a random forest object to a list of trees
applyLearner

apply a simplified tree ensemble learner (STEL) to data
buildLearner

build a simplified tree ensemble learner (STEL)