predict.cv.tropsvm {Rtropical}

Predict Method for Tropical Support Vector Machines based on Cross-Validation

Description

Predicts values based upon a model trained by cv.tropsvm.

Usage

## S3 method for class 'cv.tropsvm'
predict(object, newx, ...)

Arguments

object

a fitted "cv.tropsvm" object.

newx

a data matrix, of dimension nobs x nvars used as testing data.

...

Not used. Other arguments to predict.

Value

A vector of predicted values of a vector of labels.

See Also

summary, coef and the cv.tropsvm function.

Examples

# data generation
library(Rfast)
e <- 20
n <- 10
N <- 10
s <- 5
x <- rbind(
  rmvnorm(n, mu = c(5, -5, rep(0, e - 2)), sigma = diag(s, e)),
  rmvnorm(n, mu = c(-5, 5, rep(0, e - 2)), sigma = diag(s, e))
)
y <- as.factor(c(rep(1, n), rep(2, n)))
newx <- rbind(
  rmvnorm(N, mu = c(5, -5, rep(0, e - 2)), sigma = diag(s, e)),
  rmvnorm(N, mu = c(-5, 5, rep(0, e - 2)), sigma = diag(s, e))
)
newy <- as.factor(rep(c(1, 2), each = N))

# train the tropical svm
cv_tropsvm_fit <- cv.tropsvm(x, y, parallel = FALSE)

# test with new data
pred <- predict(cv_tropsvm_fit, newx)

# check with accuracy
table(pred, newy)

# compute testing accuracy
sum(pred == newy) / length(newy)