#' Build autoML Model
#' @export fit.automl.h2o
#' @param training A training dataset with calculated Chemical Descriptors
#' @return Returns a trained model ready to predict
#' @examples
#' \donttest{
#' aml <- fit.automl.h2o(training)}
fit.automl.h2o <- function(training, max_models = 30) {
h2o::h2o.init(nthreads = -1, strict_version_check=FALSE)
training <- h2o::as.h2o(training)
nonx <- c("Name", "InChIKey", "SMILES", "RT")
x <- setdiff(names(training), nonx)
y <- "RT"
print("Computing model autoML ... Please wait ...")
# Model training using the above parameters
aml <- h2o::h2o.automl(x = x, y = y,
training_frame = training,
nfolds = 10,
max_models = max_models,
seed = 1)
print("End training")
return(aml)
}
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