predict.ksmm: Predict Methods for Kernel Support Matrix Machines

In kyuridata/ksmm: ksmm algorithm

Description

This function predicts values based upon a model trained by ksmm

Usage

	predict.ksmm(object, new_x, nCores = 1)

Arguments

object	Object of class 'ksmm', created by ksmm
new_x	input data matrix to test
nCores	the number of cores to use for parallel computing

Details

This code is built by KSMM paper. Detailed theory is included in the KSMM paper

Author(s)

Kyuri Park

References

Ye, Y. (2019). A nonlinear kernel support matrix machine. International Journal of Machine Learning and Cybernetics.

See Also

ksmm

Examples

require(ksmm)
data(nottingham)

X = as.matrix(nottingham[,-1])
y = ifelse(nottingham[,1] == 1, 1, -1)
train_x = X[c(1,100),]
train_y = y[c(1,100)]
test_x = X[2,]
test_y = y[2]

ksmm_fit = ksmm(train_x, train_y, c(200,200), 1, 1, 'rbf', 100, 1, 5e-2)
ksmm_pred_y = predict.ksmm(object = ksmm_fit, new_x = test_x, nCores = 1)
table(ksmm_pred_y, test_y)

kyuridata/ksmm documentation built on Dec. 21, 2021, 8:47 a.m.