predict class labels for new observations

Predict the binary class labels or the fitted values of an lhsc object.

Usage

# S3 method for class 'lhsc'
predict(object, kern, x, newx, type=c("class", "link"), ...)

Arguments

object: A fitted lhsc object.
kern: The kernel function used when fitting the lhsc object.
x: The predictor matrix, i.e., the x matrix used when fitting the lhsc object.
newx: A matrix of new values for x at which predictions are to be made. We note that newx must be a matrix, predict function does not accept a vector or other formats of newx.
type: "class" or "link"? "class" produces the predicted binary class labels and "link" returns the fitted values. Default is "class".
...: Not used. Other arguments to predict.

Details

If "type" is "class", the function returns the predicted class labels. If "type" is "link", the result is \(\beta_0 + x_i'\beta\) for the linear case and \(\beta_0 + K_i'\alpha\) for the kernel case.

Value

Returns either the predicted class labels or the fitted values, depending on the choice of type.

Author

Oh-Ran Kwon and Hui Zou
Maintainer: Oh-Ran Kwon kwon0085@umn.edu

Examples

data(BUPA)
BUPA$X = scale(BUPA$X, center=TRUE, scale=TRUE)
lambda = 10^(seq(-3, 3, length.out=10))
kern = rbfdot(sigma=sigest(BUPA$X))
m1 = lhsc(BUPA$X, BUPA$y, kern,
  lambda=lambda, eps=1e-5, maxit=1e5)
predict(m1, kern, BUPA$X, tail(BUPA$X))
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,]    1    1    1    1    1    1    1    1    1     1
#> [2,]    1    1    1    1    1    1    1    1    1    -1
#> [3,]    1    1    1    1    1    1    1    1    1     1
#> [4,]    1    1    1    1    1    1    1    1    1    -1
#> [5,]    1    1    1    1    1    1    1    1    1    -1
#> [6,]    1    1    1    1    1    1    1    1    1    -1