glpls1a.train.test.error {gpls} | R Documentation |
Out-of-sample test set error for fitting IRWPLS or IRWPLSF model on the training set for two-group classification
glpls1a.train.test.error(train.X,train.y,test.X,test.y,K.prov=NULL,eps=1e-3,lmax=100,family="binomial",link="logit",br=T)
train.X |
n by p design matrix (with no intercept term) for training set |
train.y |
response vector (0 or 1) for training set |
test.X |
transpose of the design matrix (with no intercept term) for test set |
test.y |
response vector (0 or 1) for test set |
K.prov |
number of PLS components, default is the rank of train.X |
eps |
tolerance for convergence |
lmax |
maximum number of iteration allowed |
family |
glm family, binomial is the only relevant one here |
link |
link function, logit is the only one practically implemented now |
br |
TRUE if Firth's bias reduction procedure is used |
error |
out-of-sample test error |
error.obs |
the misclassified error observation indices |
predict.test |
the predicted probabilities for test set |
Beiying Ding, Robert Gentleman
glpls1a.cv.error
,
glpls1a.mlogit.cv.error
, glpls1a
, glpls1a.mlogit
, glpls1a.logit.all
x <- matrix(rnorm(20),ncol=2) y <- sample(0:1,10,TRUE) x1 <- matrix(rnorm(10),ncol=2) y1 <- sample(0:1,5,TRUE) ## no bias reduction glpls1a.train.test.error(x,y,x1,y1,br=FALSE) ## bias reduction glpls1a.train.test.error(x,y,x1,y1,br=TRUE)