predict.eztune {EZtune} | R Documentation |
Prediction function for EZtune
Description
predict.eztune
Computes predictions for a validation dataset.
Usage
## S3 method for class 'eztune'
predict(object, newdata, ...)
Arguments
object |
An object of class " |
newdata |
Matrix or data frame containing the test or validation dataset. |
... |
Additional parameters to pass to predict. |
Value
Function returns a vector of predictions if the response is
continuous. If the response is binary, a data.frame
with the predicted
response and the probabilities of each response type is returned.
Examples
library(EZtune)
data(lichen)
data(lichenTest)
y <- lichen[, 2]
x <- lichen[, 9:41]
# Optimize an SVM classification model using the default settings
mod1 <- eztune(x, y)
# Obtain predictions using the lichenTest dataset and compute classification
# error
pred <- predict(mod1, lichenTest)
mean(pred$predictions == as.factor(lichenTest$LobaOreg))
# Optimize an SVM regression model using the default settings
library(mlbench)
library(dplyr)
library(yardstick)
data(BostonHousing2)
bh <- mutate(BostonHousing2, lcrim = log(crim)) %>%
select(-town, -medv, -crim)
x <- bh[, c(1:3, 5:17)]
y <- bh[, 4]
mod2 <- eztune(x, y)
# Obtain predictions from the original data and compute the rmse
pred <- predict(mod2, x)
rmse_vec(pred, y)
[Package EZtune version 3.1.1 Index]