CGGPvalstats {CGGP} | R Documentation |
Calculate stats for CGGP prediction on validation data
CGGPvalstats(CGGP, Xval, Yval, bydim = TRUE, ...)
CGGP |
CGGP object |
Xval |
X validation matrix |
Yval |
Y validation data |
bydim |
If multiple outputs, should it be done separately by dimension? |
... |
Passed to valstats, such as which stats to calculate. |
data frame
SG <- CGGPcreate(d=3, batchsize=100) f1 <- function(x){x[1]+x[2]^2} y <- apply(SG$design, 1, f1) SG <- CGGPfit(SG, y) Xval <- matrix(runif(3*100), ncol=3) Yval <- apply(Xval, 1, f1) CGGPvalstats(CGGP=SG, Xval=Xval, Yval=Yval) # Multiple outputs SG <- CGGPcreate(d=3, batchsize=100) f1 <- function(x){x[1]+x[2]^2} f2 <- function(x){x[1]^1.3+.4*sin(6*x[2])+10} y1 <- apply(SG$design, 1, f1)#+rnorm(1,0,.01) y2 <- apply(SG$design, 1, f2)#+rnorm(1,0,.01) y <- cbind(y1, y2) SG <- CGGPfit(SG, Y=y) Xval <- matrix(runif(3*100), ncol=3) Yval <- cbind(apply(Xval, 1, f1), apply(Xval, 1, f2)) CGGPvalstats(SG, Xval, Yval) CGGPvalstats(SG, Xval, Yval, bydim=FALSE)