predict.cv.tropsvm {Rtropical} | R Documentation |
Predicts values based upon a model trained by cv.tropsvm
.
## S3 method for class 'cv.tropsvm'
predict(object, newx, ...)
object |
a fitted |
newx |
a data matrix, of dimension nobs x nvars used as testing data. |
... |
Not used. Other arguments to predict. |
A vector of predicted values of a vector of labels.
summary
, coef
and the cv.tropsvm
function.
# 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)