miceCompare

Statistically compare two models using a paired t-test and bootstrap samples of the assessment results

Usage

miceCompare(ref, result1, result2, reps)

Arguments

ref

column of reference labels as factor data type.

result1

column of predicted labels as factor data type (first result to compare).

result2

column of predicted labels as factor data type (second result to compare).

reps

number of bootstrap replicates to use. Default is 200.

Value

paired t-test results including t-statistic, degrees of freedom, p-value, 95% confidence interval, and mean difference

Examples

data(compareData)
compareResult <- miceCompare(ref=compareData$ref,
result1=compareData$rfPred,
result2=compareData$dtPred,
reps=100)
print(compareResult)
#> 
#> 	Paired t-test
#> 
#> data:  resultsDF$mice1 and resultsDF$mice2
#> t = 103.73, df = 99, p-value < 2.2e-16
#> alternative hypothesis: true mean difference is not equal to 0
#> 95 percent confidence interval:
#>  0.1033426 0.1073732
#> sample estimates:
#> mean difference 
#>       0.1053579 
#>