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#' Quickly Creating BigML Datasets
#' @export
#' @family dataset methods
#' @references \url{https://bigml.com/developers/datasets}
#' @family quick methods
#' @param data A matrix or data frame containing data to upload to bigml.
#' @param name A string giving the name for the dataset.
#' @param fields A vector of names in \code{data} that should be used for
#' creating the dataset.
#' @param size A numeric value giving the amount (in bytes) of the source
#' to use.
#' @template dots
#' @template dataset_return
#' @template author
#' @details quickDataset will take its "data" dataframe argument and attempt
#' to create an equivalent BigML dataset using \code{\link{quickSource}}.
#' R "numeric" class fields will become "numeric" fields in the BigML
#' dataset. R "character" class fields become "text" fields. R "factor"
#' fields become "categorical" fields. However, if there are too many
#' factors, BigML may convert the field to text. It is possible to specify
#' the fields to include using the \code{fields} argument. This can be a
#' a simple list of names that were present in the \code{data} argument.
#' See references for more details.
#' @examples
#' \dontrun{
#' # simple example
#' iris.d = quickDataset(iris)
#' # configure a number of different parameters
#' iris.d2 = quickDataset(iris, fields = c('Species', 'Sepal.length'),
#' name='test', size=10000)
#' }
quickDataset <-
function (data, fields = names(data), name = paste(deparse(substitute(data)),
"'s dataset", sep = ""), size = NULL, ...)
{
option = list()
sresponse = quickSource(data, name = deparse(substitute(data)),
flatten = F, ...)
if (is.null(name))
name = paste(sresponse$file_name, "'s dataset", sep = "")
classes = lapply(data, class)
type_classes = lapply(classes, function(x) {
if (x == "numeric")
return("numeric")
else if (x == "factor")
return("categorical")
else return("text")
})
option$name = name
option$source = sresponse$resource
if (is.null(size))
option$size = size
message("Dataset creation in progress...")
return(.basic_api(.DATASET_URL)$postJson(option, ...))
}
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