x <- matrix(rnorm(100*5),ncol=5)
c <- 2*x[,1]
p <- exp(c)/(exp(c)+exp(-c))
y <- rbinom(100,1,p)
y[y != 1] <- -1
y[1:10] <- -y[1:10]
x <- as.data.frame(x)
dat.m <- bst(x, y, ctrl = bst_control(mstop=50), family = "hinge", learner = "ls")
predict(dat.m)
dat.m1 <- bst(x, y, ctrl = bst_control(twinboost=TRUE,
coefir=coef(dat.m), xselect.init = dat.m$xselect, mstop=50))
dat.m2 <- rbst(x, y, ctrl = bst_control(mstop=50, s=0, trace=TRUE),
rfamily = "thinge", learner = "ls")
predict(dat.m2)
rmstop <- seq(10, 40, by=10)
dat.m3 <- rbstpath(x, y, rmstop, ctrl=bst_control(s=0), rfamily = "thinge", learner = "ls")
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