setDecisionTree: Create setting for DecisionTree with python

In hxia/plp-git-demo: Package for patient level prediction using data in the OMOP Common Data Model

Description

Create setting for DecisionTree with python

Usage

setDecisionTree(
  maxDepth = 10,
  minSamplesSplit = 2,
  minSamplesLeaf = 10,
  minImpurityDecrease = 10^-7,
  seed = NULL,
  classWeight = "None",
  plot = F
)

Arguments

maxDepth	The maximum depth of the tree
minSamplesSplit	The minimum samples per split
minSamplesLeaf	The minimum number of samples per leaf
minImpurityDecrease	Threshold for early stopping in tree growth. A node will split if its impurity is above the threshold, otherwise it is a leaf.
seed	The random state seed
classWeight	Balance or None
plot	Boolean whether to plot the tree (requires python pydotplus module)

Examples

## Not run: 
model.decisionTree <- setDecisionTree(maxDepth=10,minSamplesLeaf=10, seed=NULL )

## End(Not run)

hxia/plp-git-demo documentation built on March 19, 2021, 1:54 a.m.