predict.stackgbm {stackgbm}

Make predictions from a stackgbm model object

Description

Make predictions from a stackgbm model object

Usage

## S3 method for class 'stackgbm'
predict(object, newx, threshold = 0.5, classes = c(1L, 0L), ...)

Arguments

object

A stackgbm model object.

newx

New predictor matrix.

threshold

Decision threshold. Default is 0.5.

classes

The class encoding vector of the predicted outcome. The naming and order will be respected.

...

Unused.

Value

A list of two vectors presenting the predicted classification probabilities and predicted response.

Examples

sim_data <- msaenet::msaenet.sim.binomial(
  n = 1000,
  p = 50,
  rho = 0.6,
  coef = rnorm(25, mean = 0, sd = 10),
  snr = 1,
  p.train = 0.8,
  seed = 42
)

params_xgboost <- structure(
  list("nrounds" = 200, "eta" = 0.05, "max_depth" = 3),
  class = c("cv_params", "cv_xgboost")
)
params_lightgbm <- structure(
  list("num_iterations" = 200, "max_depth" = 3, "learning_rate" = 0.05),
  class = c("cv_params", "cv_lightgbm")
)
params_catboost <- structure(
  list("iterations" = 100, "depth" = 3),
  class = c("cv_params", "cv_catboost")
)

fit <- stackgbm(
  sim_data$x.tr,
  sim_data$y.tr,
  params = list(
    params_xgboost,
    params_lightgbm,
    params_catboost
  )
)

predict(fit, newx = sim_data$x.te)