Description Usage Arguments Value Author(s) References See Also Examples
For a set of n observations grouped into two classes (for
example n expression values of a gene), the margin
function measures the size of the gap between the classes. This is the
distance between the observation of response class zero having the
lowest value, and the individual of with response one having the
highest value.
1 | margin(x, resp)
|
x |
Numeric vector of length n, for example containing gene or cluster expression values of n different cases. |
resp |
Numeric vector of length n containing the “binary”
class labels of the cases. Must be coded by |
A numeric value, the margin
. Positive margin
indicates perfect separation of the response classes, whereas negative
margin
means imperfect separation.
Marcel Dettling
see those in wilma
.
wilma
, score
is the second statistic
that is used there.
1 2 3 4 5 6 7 8 9 10 11 12 | data(leukemia, package="supclust")
op <- par(mfrow=c(1,3))
plot(leukemia.x[,69],leukemia.y)
title(paste("Margin = ", round(margin(leukemia.x[,69], leukemia.y),2)))
## Sign-flipping is very important
plot(leukemia.x[,161],leukemia.y)
title(paste("Margin = ", round(margin(leukemia.x[,161], leukemia.y),2)))
x <- sign.flip(leukemia.x, leukemia.y)$flipped.matrix
plot(x[,161],leukemia.y)
title(paste("Margin = ", round(margin(x[,161], leukemia.y),2)))
par(op)
|
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