LOGANTree (version 0.1.1)

ChiSquareTable: Chi-square Statistics Table

Description

Chi-square Statistics Table

Usage

ChiSquareTable(
  trainingdata = NULL,
  nfeatureNames = NULL,
  outcome = NULL,
  level = NULL,
  ModelObject = NULL
)

Arguments

trainingdata

A data set used for training

nfeatureNames

A vector of feature names that will be used for computing chi-square statistics

outcome

A character string with the name of the binary outcome variable.

level

A numerical value indicating the number of categories that the outcome contains

ModelObject

A model object containing tree-based models

Value

This function returns a table with five columns. The chi-square statistics were computed as described by He & von Davier (2015).

Feature: Features names

CvAverageChisq: Average chisquare statistics computed from 10-fold cross validation samples

Rank.CvAverageChisq: Ordem of the feature importance from the CvAverageChisq measures#'

OverallChisq: chisquare scores computed from the whole training sample

Rank.OverallChisq: Ordem of the feature importance from the OverallChisq measures

References

He, Q., & von Davier, M. (2015). Identifying feature sequences from process data in problem-solving items with N-grams. In Quantitative Psychology Research: The 79th Annual Meeting of the Psychometric Society (pp. 173<U+2013>190). Madison, Wisconsin: Springer International Publishing.

Examples

# NOT RUN {
colnames(training)[14] <- "perf"
ensemblist <- TreeModels(traindata = training,
methodlist = c("dt", "gbm"),checkprogress = TRUE)

ChiSquareTable(trainingdata=training,
nfeatureNames=colnames(training[,7:13]),
outcome = "perf",level = 2, ModelObject = ensemblist$ModelObject)
# }