[R-package] Rename `data` -> `newdata` in `predict()` (#4973)

R-package/R/lgb.Booster.R

@@ -713,7 +713,7 @@ Booster <- R6::R6Class(
 #' @title Predict method for LightGBM model
 #' @description Predicted values based on class \code{lgb.Booster}
 #' @param object Object of class \code{lgb.Booster}
-#' @param data a \code{matrix} object, a \code{dgCMatrix} object or
+#' @param newdata a \code{matrix} object, a \code{dgCMatrix} object or
 #'                a character representing a path to a text file (CSV, TSV, or LibSVM)
 #' @param start_iteration int or None, optional (default=None)
 #'                        Start index of the iteration to predict.
@@ -779,7 +779,7 @@ Booster <- R6::R6Class(
 #' @importFrom utils modifyList
 #' @export
 predict.lgb.Booster <- function(object,
-                                data,
+                                newdata,
                                 start_iteration = NULL,
                                 num_iteration = NULL,
                                 rawscore = FALSE,
@@ -805,7 +805,7 @@ predict.lgb.Booster <- function(object,
 
   return(
     object$predict(
-      data = data
+      data = newdata
       , start_iteration = start_iteration
       , num_iteration = num_iteration
       , rawscore = rawscore

R-package/man/predict.lgb.Booster.Rd

@@ -6,7 +6,7 @@
 \usage{
 \method{predict}{lgb.Booster}(
   object,
-  data,
+  newdata,
   start_iteration = NULL,
   num_iteration = NULL,
   rawscore = FALSE,
@@ -21,7 +21,7 @@
 \arguments{
 \item{object}{Object of class \code{lgb.Booster}}
 
-\item{data}{a \code{matrix} object, a \code{dgCMatrix} object or
+\item{newdata}{a \code{matrix} object, a \code{dgCMatrix} object or
 a character representing a path to a text file (CSV, TSV, or LibSVM)}
 
 \item{start_iteration}{int or None, optional (default=None)

R-package/tests/testthat/test_Predictor.R

@@ -79,7 +79,7 @@ test_that("start_iteration works correctly", {
         , early_stopping_rounds = 2L
     )
     expect_true(lgb.is.Booster(bst))
-    pred1 <- predict(bst, data = test$data, rawscore = TRUE)
+    pred1 <- predict(bst, newdata = test$data, rawscore = TRUE)
     pred_contrib1 <- predict(bst, test$data, predcontrib = TRUE)
     pred2 <- rep(0.0, length(pred1))
     pred_contrib2 <- rep(0.0, length(pred2))