#' @export
makeRLearner.classif.parallelForest = function() {
makeRLearnerClassif(
cl = "classif.parallelForest",
package = "!ParallelForest",
par.set = makeParamSet(
##For all the parameters here package manual states:
##If not provided as input, the package will attempt to choose a reasonable value
makeIntegerLearnerParam(id = "min_node_obs", lower = 1L),
makeIntegerLearnerParam(id = "max_depth", lower = 1L),
makeIntegerLearnerParam(id = "numsamps", lower = 1L),
makeIntegerLearnerParam(id = "numvars", lower = 1L),
makeIntegerLearnerParam(id = "numboots", lower = 1L)
),
properties = c("twoclass", "numerics"),
name = "Parallel Random Forest",
short.name = "parallelForest"
)
}
#' @export
trainLearner.classif.parallelForest = function(.learner, .task, .subset, .weights = NULL, ...) {
f = getTaskFormula(.task)
df = getTaskData(.task, .subset)
ParallelForest::grow.forest(formula = f, data = df, na.action = na.omit,
impurity.function = "gini", model = FALSE, x = FALSE, y = FALSE, ...)
}
#' @export
predictLearner.classif.parallelForest = function(.learner, .model, .newdata, ...) {
predict(.model$learner.model, newdata = .newdata, ...)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.