Nothing
model
argumentCode
set_pred("light")
Error <rlang_error>
Model `light` has not been registered.
Code
set_pred(model = c("tent", "shed"), mode = "partition", eng = "stats", type = "raw",
value = list(pre = NULL, post = NULL, func = c(fun = "predict"), args = list(
object = rlang::expr(object$fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
Please supply a character string for a model name (e.g. `'k_means'`).
mode
argumentCode
set_pred("game")
Error <rlang_error>
Please supply a character string for a mode (e.g. `'partition'`).
Code
set_pred("game", c("classification", "regression"))
Error <rlang_error>
Please supply a character string for a mode (e.g. `'partition'`).
Code
set_pred("game", NULL)
Error <rlang_error>
Please supply a character string for a mode (e.g. `'partition'`).
Code
set_pred(model = "game", mode = "not partition", eng = "stats", type = "raw",
value = list(pre = NULL, post = NULL, func = c(fun = "predict"), args = list(
object = rlang::expr(object$fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
'not partition' is not a known mode for model `game()`.
engine
argumentCode
set_pred("dog", "partition")
Error <rlang_error>
Please supply a character string for an engine name (e.g. `'stats'`).
Code
set_pred("dog", "partition", c("glmnet", "stats"))
Error <rlang_error>
Please supply a character string for an engine name (e.g. `'stats'`).
Code
set_model_engine("dog", "partition", NULL)
Error <rlang_error>
Please supply a character string for an engine name (e.g. `'stats'`).
value
argumentCode
set_pred("trunk", "partition", "stats", "raw")
Error <simpleError>
argument "value" is missing, with no default
Code
set_pred("trunk", "partition", "stats", "raw", NULL)
Error <rlang_error>
The `predict` module should have elements: `args`, `func`, `post`, `pre`
Code
set_pred(model = "trunk", mode = "partition", eng = "stats", type = "raw",
value = list(post = NULL, func = c(fun = "predict"), args = list(object = rlang::expr(
object$fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
The `predict` module should have elements: `args`, `func`, `post`, `pre`
Code
set_pred(model = "trunk", mode = "partition", eng = "stats", type = "raw",
value = list(pre = NULL, func = c(fun = "predict"), args = list(object = rlang::expr(
object$fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
The `predict` module should have elements: `args`, `func`, `post`, `pre`
Code
set_pred(model = "trunk", mode = "partition", eng = "stats", type = "raw",
value = list(pre = NULL, post = NULL, args = list(object = rlang::expr(object$
fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
The `predict` module should have elements: `args`, `func`, `post`, `pre`
Code
set_pred(model = "trunk", mode = "partition", eng = "stats", type = "raw",
value = list(pre = NULL, post = NULL, func = c(fun = "predict")))
Error <rlang_error>
The `predict` module should have elements: `args`, `func`, `post`, `pre`
Code
set_pred(model = "trunk", mode = "partition", eng = "stats", type = "raw",
value = list(pre = "NULL", post = NULL, func = c(fun = "predict"), args = list(
object = rlang::expr(object$fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
The `pre` module should be null or a function:
Code
set_pred(model = "trunk", mode = "partition", eng = "stats", type = "raw",
value = list(pre = NULL, post = "NULL", func = c(fun = "predict"), args = list(
object = rlang::expr(object$fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
The `post` module should be null or a function:
Code
set_pred(model = "trunk", mode = "partition", eng = "stats", type = "raw",
value = list(pre = NULL, post = NULL, func = c(fun = "predict"), args = "not a list"))
Error <rlang_error>
The `args` element should be a list.
type
argumentCode
set_pred(model = "scroll", mode = "partition", eng = "stats", type = "not raw",
value = list(pre = NULL, post = NULL, func = c(fun = "predict"), args = list(
object = rlang::expr(object$fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
The prediction type should be one of: 'cluster', 'raw'
Code
set_pred(model = "diamond", mode = "partition", eng = "stats", type = "raw",
value = list(pre = NULL, post = NULL, func = c(fun = "not predict"), args = list(
object = rlang::expr(object$fit), newdata = rlang::expr(new_data), type = "response")))
Error <rlang_error>
The combination of engine 'stats' and mode 'partition' and prediction type 'raw' already has predict data for model 'diamond' and the new information being registered is different.
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