Plot histogram of the MCC classes

This function is a wrapper of the ahist function for plotting nicely the distribution of the MCC models' values.

plot_mcc_classes_hist(models.mcc, models.cluster.ids, num.of.mcc.classes)

Arguments

models.mcc	a numeric vector of Matthews Correlation Coefficient (MCC) scores, one for each model. The names attribute may hold the models' names (but it is not required).
models.cluster.ids	a numeric vector of cluster ids assigned to each model. It can be the result of using Ckmeans.1d.dp with input the models' MCC values (models.mcc) and the number of clusters (num.of.mcc.classes).
num.of.mcc.classes	numeric. A positive integer (>2) that signifies the number of mcc classes (groups) that we should split the models MCC values.

Examples

models.mcc = c(-0.04, -0.17, 0.15, -0.24, -0.02 , 0.27, -0.42 , 0.38)
models.cluster.ids = c(2,2,3,1,2,3,1,3)
num.of.mcc.classes = 3
plot_mcc_classes_hist(models.mcc, models.cluster.ids, num.of.mcc.classes)
#> [1] TRUE