Tools for models that predict on sub-models
has_multi_predict() tests to see if an object can make multiple
predictions on submodels from the same object. multi_predict_args()
returns the names of the arguments to multi_predict() for this model
(if any).
has_multi_predict(object, ...) ## Default S3 method: has_multi_predict(object, ...) ## S3 method for class 'model_fit' has_multi_predict(object, ...) ## S3 method for class 'workflow' has_multi_predict(object, ...) multi_predict_args(object, ...) ## Default S3 method: multi_predict_args(object, ...) ## S3 method for class 'model_fit' multi_predict_args(object, ...) ## S3 method for class 'workflow' multi_predict_args(object, ...)
object |
An object to test. |
... |
Not currently used. |
has_multi_predict() returns single logical value while
multi_predict() returns a character vector of argument names (or NA
if none exist).
lm_model_idea <- linear_reg() %>% set_engine("lm")
has_multi_predict(lm_model_idea)
lm_model_fit <- fit(lm_model_idea, mpg ~ ., data = mtcars)
has_multi_predict(lm_model_fit)
multi_predict_args(lm_model_fit)
library(kknn)
knn_fit <-
nearest_neighbor(mode = "regression", neighbors = 5) %>%
set_engine("kknn") %>%
fit(mpg ~ ., mtcars)
multi_predict_args(knn_fit)
multi_predict(knn_fit, mtcars[1, -1], neighbors = 1:4)$.predPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.