R/ml_feature_vector_assembler.R

Defines functions validator_ml_vector_assembler new_ml_vector_assembler ft_vector_assembler.tbl_spark ft_vector_assembler.ml_pipeline ft_vector_assembler.spark_connection ft_vector_assembler

Documented in ft_vector_assembler

#' Feature Transformation -- VectorAssembler (Transformer)
#'
#' Combine multiple vectors into a single row-vector; that is,
#' where each row element of the newly generated column is a
#' vector formed by concatenating each row element from the
#' specified input columns.
#'
#' @param input_cols The names of the input columns
#' @param output_col The name of the output column.
#' @template roxlate-ml-feature-transformer
#'
#' @export
ft_vector_assembler <- function(x, input_cols = NULL, output_col = NULL,
                                uid = random_string("vector_assembler_"), ...) {
  check_dots_used()
  UseMethod("ft_vector_assembler")
}

ml_vector_assembler <- ft_vector_assembler

#' @export
ft_vector_assembler.spark_connection <- function(x, input_cols = NULL, output_col = NULL,
                                                 uid = random_string("vector_assembler_"), ...) {
  .args <- list(
    input_cols = input_cols,
    output_col = output_col,
    uid = uid
  ) %>%
    c(rlang::dots_list(...)) %>%
    validator_ml_vector_assembler()

  jobj <- spark_pipeline_stage(
    x, "org.apache.spark.ml.feature.VectorAssembler",
    input_cols = .args[["input_cols"]], output_col = .args[["output_col"]], uid = .args[["uid"]]
  )

  new_ml_vector_assembler(jobj)
}

#' @export
ft_vector_assembler.ml_pipeline <- function(x, input_cols = NULL, output_col = NULL,
                                            uid = random_string("vector_assembler_"), ...) {
  stage <- ft_vector_assembler.spark_connection(
    x = spark_connection(x),
    input_cols = input_cols,
    output_col = output_col,
    uid = uid,
    ...
  )
  ml_add_stage(x, stage)
}

#' @export
ft_vector_assembler.tbl_spark <- function(x, input_cols = NULL, output_col = NULL,
                                          uid = random_string("vector_assembler_"), ...) {
  stage <- ft_vector_assembler.spark_connection(
    x = spark_connection(x),
    input_cols = input_cols,
    output_col = output_col,
    uid = uid,
    ...
  )
  ml_transform(stage, x)
}

new_ml_vector_assembler <- function(jobj) {
  new_ml_transformer(jobj, class = "ml_vector_assembler")
}

validator_ml_vector_assembler <- function(.args) {
  .args <- validate_args_transformer(.args)
  .args
}

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sparklyr documentation built on Jan. 8, 2022, 5:06 p.m.