inTrees v1.2


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Interpret Tree Ensembles

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.

Functions in inTrees

Name Description
selectRuleRRF select a set of relevant and non-redundant rules
ruleList2Exec internal
measureRule internal
getFreqPattern calculate frequent variable interactions
treeVisit internal function
sortRule internal
voteAllRules internal
singleRuleList2Exec internal
extractRules Extract rules from a list of trees
dataSimulate Simulate data
buildLearner build a simplified tree ensemble learner (STEL)
Num2Level internal function
dicretizeVector discretize a variable
applyLearner apply a simplified tree ensemble learner (STEL) to data
XGB2List Transform an xgboost object to a list of trees
GBM2List Transform gbm object to a list of trees
computeRuleInfor compute rule information
presentRules Present a learner using column names instead of X[i,]
getTypeX get type of each variable
getRuleMetric Assign outcomes to a conditions, and measure the rules
rule2Table internal function
pruneSingleRule internal
lookupRule internal
formatGBM internal
RF2List Transform a random forest object to a list of trees
pruneRule Prune irrevant variable-value pair from a rule condition
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Date 2018-03-10
License GPL (>= 3)
Packaged 2018-03-12 04:55:28 UTC; houtaodeng
NeedsCompilation no
Repository CRAN
Date/Publication 2018-03-12 05:35:13 UTC

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