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#' Tidying methods for Spark ML Isotonic Regression
#'
#' These methods summarize the results of Spark ML models into tidy forms.
#'
#' @param x a Spark ML model.
#' @param ... extra arguments (not used.)
#' @name ml_isotonic_regression_tidiers
NULL
#' @rdname ml_isotonic_regression_tidiers
#' @export
tidy.ml_model_isotonic_regression <- function(x,
...) {
dplyr::tibble(
boundaries = x$model$boundaries(),
predictions = x$model$predictions()
)
}
#' @rdname ml_isotonic_regression_tidiers
#' @param newdata a tbl_spark of new data to use for prediction.
#'
#' @export
augment.ml_model_isotonic_regression <- function(x, newdata = NULL,
...) {
broom_augment_supervised(x, newdata = newdata)
}
#' @rdname ml_isotonic_regression_tidiers
#' @export
glance.ml_model_isotonic_regression <- function(x, ...) {
isotonic <- x$model$param_map$isotonic
num_boundaries <- length(x$model$boundaries())
dplyr::tibble(
isotonic = isotonic,
num_boundaries = num_boundaries
)
}
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