combined.aov <- aov(AUC ~ features, combined)
summary(combined.aov)
## Df Sum Sq Mean Sq F value Pr(>F)
## features 6 1.6275 0.2712 306741 <2e-16 ***
## Residuals 168 0.0001 0.0000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
HSD.test(combined.aov, "features", console = TRUE)
##
## Study: combined.aov ~ "features"
##
## HSD Test for AUC
##
## Mean Square Error: 8.842712e-07
##
## features, means
##
## AUC std r Min Max
## all 0.9604316 0.0004776338 25 0.9596673 0.9612425
## behavior 0.9491307 0.0005427855 25 0.9481725 0.9498628
## behavior-network 0.9581083 0.0004253070 25 0.9574684 0.9588556
## behavior-text 0.9518454 0.0005522874 25 0.9509084 0.9525870
## network 0.7089728 0.0014375619 25 0.7071942 0.7121525
## network-text 0.8467852 0.0011093575 25 0.8447357 0.8482490
## text 0.7692391 0.0013725823 25 0.7681056 0.7723861
##
## alpha: 0.05 ; Df Error: 168
## Critical Value of Studentized Range: 4.220582
##
## Honestly Significant Difference: 0.0007937708
##
## Means with the same letter are not significantly different.
##
## Groups, Treatments and means
## a all 0.9604
## b behavior-network 0.9581
## c behavior-text 0.9518
## d behavior 0.9491
## e network-text 0.8468
## f text 0.7692
## g network 0.709
tukeyPlot(combined, groupVars = "features")
