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#' Feature Transformation -- NGram (Transformer)
#'
#' A feature transformer that converts the input array of strings into an array of n-grams. Null values in the input array are ignored. It returns an array of n-grams where each n-gram is represented by a space-separated string of words.
#'
#' @details When the input is empty, an empty array is returned. When the input array length is less than n (number of elements per n-gram), no n-grams are returned.
#'
#' @template roxlate-ml-feature-input-output-col
#' @template roxlate-ml-feature-transformer
#' @param n Minimum n-gram length, greater than or equal to 1. Default: 2, bigram features
#'
#' @export
ft_ngram <- function(x, input_col = NULL, output_col = NULL, n = 2,
uid = random_string("ngram_"), ...) {
check_dots_used()
UseMethod("ft_ngram")
}
ml_ngram <- ft_ngram
#' @export
ft_ngram.spark_connection <- function(x, input_col = NULL, output_col = NULL, n = 2,
uid = random_string("ngram_"), ...) {
.args <- list(
input_col = input_col,
output_col = output_col,
n = n,
uid = uid
) %>%
c(rlang::dots_list(...)) %>%
validator_ml_ngram()
jobj <- spark_pipeline_stage(
x, "org.apache.spark.ml.feature.NGram",
input_col = .args[["input_col"]], output_col = .args[["output_col"]], uid = .args[["uid"]]
) %>%
invoke("setN", .args[["n"]])
new_ml_ngram(jobj)
}
#' @export
ft_ngram.ml_pipeline <- function(x, input_col = NULL, output_col = NULL, n = 2,
uid = random_string("ngram_"), ...) {
stage <- ft_ngram.spark_connection(
x = spark_connection(x),
input_col = input_col,
output_col = output_col,
n = n,
uid = uid,
...
)
ml_add_stage(x, stage)
}
#' @export
ft_ngram.tbl_spark <- function(x, input_col = NULL, output_col = NULL, n = 2,
uid = random_string("ngram_"), ...) {
stage <- ft_ngram.spark_connection(
x = spark_connection(x),
input_col = input_col,
output_col = output_col,
n = n,
uid = uid,
...
)
ml_transform(stage, x)
}
new_ml_ngram <- function(jobj) {
new_ml_transformer(jobj, class = "ml_ngram")
}
validator_ml_ngram <- function(.args) {
.args <- validate_args_transformer(.args)
.args[["n"]] <- cast_scalar_integer(.args[["n"]])
.args
}
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