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(R) Make 'predict' an S3 method #1657

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(R) Make 'predict' an S3 method #1657

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b758106
make predict an S3 method
david-cortes Apr 18, 2021
fb19e12
missing import for generic predict
david-cortes Apr 18, 2021
071ce08
Merge branch 'master' into predict_as_s3
kizill Sep 29, 2021
e63749f
Update NAMESPACE
david-cortes Sep 29, 2021
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2 changes: 2 additions & 0 deletions catboost/R-package/NAMESPACE
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
S3method(dim,catboost.Pool)
S3method(dimnames,catboost.Pool)
S3method(head,catboost.Pool)
S3method(predict,catboost.Model)
S3method(print,catboost.Model)
S3method(print,catboost.Pool)
S3method(summary,catboost.Model)
Expand All @@ -27,6 +28,7 @@ export(catboost.sum_models)
export(catboost.train)
export(catboost.virtual_ensembles_predict)
import(jsonlite)
importFrom(stats,predict)
importFrom(utils,download.file)
importFrom(utils,head)
importFrom(utils,tail)
Expand Down
40 changes: 31 additions & 9 deletions catboost/R-package/R/catboost.R
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
#' @import jsonlite
#' @importFrom stats predict
#' @importFrom utils head
#' @importFrom utils tail
#' @importFrom utils write.table
Expand Down Expand Up @@ -1785,16 +1786,19 @@ catboost.save_model <- function(model, model_path,


#' @name catboost.predict
#' @title Apply the model
#' @title Get predictions from a CatBoost model
#'
#' @description Apply the model to the given dataset.
#' @description Get predictions from a CatBoost model on new data.
#' @details The function `catboost.predict` is a synonym for `predict.catboost.Model`,
#' which is an S3 method (i.e. called like `predict(model, newdata)`).
#'
#' Peculiarities: In case of multiclassification the prediction is returned in the form of a matrix.
#' Each line of this matrix contains the predictions for one object of the input dataset.
#' @param model The model obtained as the result of training.
#' In case of multiclassification the prediction is returned in the form of a matrix.
#' Each row of this matrix contains the predictions for one row of the input dataset.
#' @param object The model obtained as the result of training.
#'
#' Default value: Required argument
#' @param pool The input dataset.
#' @param newdata The input data on which to make predictions. Should be a `catboost.Pool`
#' object.
#'
#' Default value: Required argument
#' @param verbose Verbose output to stdout.
Expand Down Expand Up @@ -1828,9 +1832,12 @@ catboost.save_model <- function(model, model_path,
#' @return Vector of predictions (matrix for multi-class classification).
#' @export
#' @seealso \url{https://catboost.ai/docs/concepts/r-reference_catboost-predict.html}
catboost.predict <- function(model, pool,

predict.catboost.Model <- function(model, pool,
verbose = FALSE, prediction_type = "RawFormulaVal",
ntree_start = 0, ntree_end = 0, thread_count = -1) {
if (!inherits(model, "catboost.Model"))
stop("Expected catboost.Model, got: ", class(model))
if (!inherits(pool, "catboost.Pool"))
stop("Expected catboost.Pool, got: ", class(pool))
if (is.null.handle(pool))
Expand All @@ -1839,12 +1846,27 @@ catboost.predict <- function(model, pool,
catboost.restore_handle(model)
prediction <- .Call("CatBoostPredictMulti_R", model$cpp_obj$handle, pool,
verbose, prediction_type, ntree_start, ntree_end, thread_count)
if (length(prediction) != nrow(pool)) {
prediction <- matrix(prediction, nrow = nrow(pool), byrow = TRUE)
if (length(prediction) != nrow(newdata)) {
prediction <- matrix(prediction, nrow = nrow(newdata), byrow = TRUE)
}
return(prediction)
}

#' @rdname catboost.predict
#' @export
#' @usage catboost.predict(
#' object,
#' newdata,
#' verbose = FALSE,
#' prediction_type = "RawFormulaVal",
#' ntree_start = 0,
#' ntree_end = 0,
#' thread_count = -1
#' )
catboost.predict <- function(...) {
return(predict.catboost.Model(...))
}


#' @name catboost.staged_predict
#' @title Apply the model for each tree
Expand Down
32 changes: 24 additions & 8 deletions catboost/R-package/man/catboost.predict.Rd
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