The following examples illustrate the typical behaviour of the clover plot and the different classifiers in situations discussed in Tables 5 and 6 in the paper.

Example 1:

In this example we generate observations from the shifted bivariate normal distributions with the same covariance matrix. The first sample contains 50 observations, the second sample contains 200 observations.

library(mvtnorm)

n1 <- 50
n2 <- 200

set.seed(10)

x <- rmvnorm(n=n1, mean=c(0,0), sigma=diag(2))
y <- rmvnorm(n=n2, mean=c(2,2), sigma=diag(2))

res <- clover_calc(x, y, boundaryI=FALSE)
clover_plot_data(res)
clover_plot(res, classifiers=c("DD1","DD0","QDA","BB0","BB1","II1","II0"))
## Misclassification rate of the QDA classifier:   0.088
## Non-classification rate of the QDA classifier:  0
## 
## Misclassification rate of the DD0 (max-depth) classifier:   0.064
## Non-classification rate of the DD0 (max-depth) classifier:  0.08
## 
## Misclassification rate of the DD1 classifier:   0.048
## Non-classification rate of the DD1 classifier:  0.072
## 
## Misclassification rate of the BB0 classifier:   0.092
## Non-classification rate of the BB0 classifier:  0
## 
## Misclassification rate of the BB1 classifier:   0.052
## Non-classification rate of the BB1 classifier:  0
## 
## Misclassification rate of the II0 classifier:   0.092
## Non-classification rate of the II0 classifier:  0
## 
## Misclassification rate of the II1 classifier:   0.076
## Non-classification rate of the II1 classifier:  0

Example 2:

In this example we generate observations from the shifted bivariate normal distributions with different covariance matrices.

n1 <- 200
n2 <- 200

set.seed(12)

x <- rmvnorm(n=n1,mean=c(0,0),sigma=diag(2))
y <- rmvnorm(n=n2,mean=c(2,2),sigma=9*diag(2))

res <- clover_calc(x, y, boundaryI=FALSE)
clover_plot_data(res)
clover_plot(res, classifiers=c("DD1","DD0","QDA","BB0","BB1","II1","II0"))
## Misclassification rate of the QDA classifier:   0.185
## Non-classification rate of the QDA classifier:  0
## 
## Misclassification rate of the DD0 (max-depth) classifier:   0.32
## Non-classification rate of the DD0 (max-depth) classifier:  0.0225
## 
## Misclassification rate of the DD1 classifier:   0.12
## Non-classification rate of the DD1 classifier:  0.02
## 
## Misclassification rate of the BB0 classifier:   0.2075
## Non-classification rate of the BB0 classifier:  0
## 
## Misclassification rate of the BB1 classifier:   0.1675
## Non-classification rate of the BB1 classifier:  0
## 
## Misclassification rate of the II0 classifier:   0.2275
## Non-classification rate of the II0 classifier:  0.26
## 
## Misclassification rate of the II1 classifier:   0.21
## Non-classification rate of the II1 classifier:  0.26

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