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remove uses of predict(reshape = TRUE) for lightgbm models (fixes #40) #41

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Jul 18, 2022
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remove uses of predict(reshape = TRUE) for lightgbm models (fixes #40) #41

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9703624
remove uses of predict(reshape = TRUE) for lightgbm models (fixes #40)
jameslamb Jul 17, 2022
ee75905
Update R/lightgbm.R
jameslamb Jul 18, 2022
f1cd10a
fix tests
jameslamb Jul 18, 2022
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23 changes: 20 additions & 3 deletions R/lightgbm.R
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Original file line number Diff line number Diff line change
Expand Up @@ -260,6 +260,22 @@ sort_args <- function(args) {
args
}

# in lightgbm <= 3.3.2, predict() for multiclass classification produced a single
# vector of length num_observations * num_classes, in row-major order
#
# in versions after that release, lightgbm produces a numeric matrix with shape
# [num_observations, num_classes]
#
# this function ensures that multiclass classification predictions are always
# returned as a [num_observations, num_classes] matrix, regardless of lightgbm version
reshape_lightgbm_multiclass_preds <- function(preds, num_rows) {
n_preds_per_case <- length(preds) / num_rows
if (is.vector(preds) && n_preds_per_case > 1) {
preds <- matrix(preds, ncol = n_preds_per_case, byrow = TRUE)
}
preds
}

#' Internal functions
#'
#' Not intended for direct use.
Expand All @@ -268,7 +284,8 @@ sort_args <- function(args) {
#' @export
#' @rdname lightgbm_helpers
predict_lightgbm_classification_prob <- function(object, new_data, ...) {
p <- stats::predict(object$fit, prepare_df_lgbm(new_data), reshape = TRUE, ...)
p <- stats::predict(object$fit, prepare_df_lgbm(new_data), ...)
p <- reshape_lightgbm_multiclass_preds(preds = p, num_rows = nrow(new_data))

if(is.vector(p)) {
p <- tibble::tibble(p1 = 1 - p, p2 = p)
Expand All @@ -294,7 +311,8 @@ predict_lightgbm_classification_class <- function(object, new_data, ...) {
#' @export
#' @rdname lightgbm_helpers
predict_lightgbm_classification_raw <- function(object, new_data, ...) {
stats::predict(object$fit, prepare_df_lgbm(new_data), reshape = TRUE, rawscore = TRUE, ...)
p <- stats::predict(object$fit, prepare_df_lgbm(new_data), rawscore = TRUE, ...)
reshape_lightgbm_multiclass_preds(preds = p, num_rows = nrow(new_data))
}

#' @keywords internal
Expand All @@ -305,7 +323,6 @@ predict_lightgbm_regression_numeric <- function(object, new_data, ...) {
stats::predict(
object$fit,
prepare_df_lgbm(new_data),
reshape = TRUE,
params = list(predict_disable_shape_check = TRUE),
...
)
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4 changes: 3 additions & 1 deletion tests/testthat/test-lightgbm.R
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Expand Up @@ -172,7 +172,9 @@ test_that("boost_tree with lightgbm",{
verbose = -1
)

lgbm_preds_4 <- predict(lgbm_fit_4, peng_m_c, reshape = TRUE)
lgbm_preds_4 <-
predict(lgbm_fit_4, peng_m_c) %>%
reshape_lightgbm_multiclass_preds(num_rows = nrow(peng_m_c))

expect_equal(pars_preds_4_mtx, lgbm_preds_4)

Expand Down