create_model_grid {modeltime} | R Documentation |
Helper to make parsnip
model specs from a dials
parameter grid
Description
Helper to make parsnip
model specs from a dials
parameter grid
Usage
create_model_grid(grid, f_model_spec, engine_name, ..., engine_params = list())
Arguments
grid |
A tibble that forms a grid of parameters to adjust |
f_model_spec |
A function name (quoted or unquoted) that
specifies a |
engine_name |
A name of an engine to use. Gets passed to |
... |
Static parameters that get passed to the f_model_spec |
engine_params |
A |
Details
This is a helper function that combines dials
grids with
parsnip
model specifications. The intent is to make it easier
to generate workflowset
objects for forecast evaluations
with modeltime_fit_workflowset()
.
The process follows:
Generate a grid (hyperparemeter combination)
Use
create_model_grid()
to apply the parameter combinations to a parsnip model spec and engine.
The output contains ".model" column that can be used as a list
of models inside the workflow_set()
function.
Value
Tibble with a new colum named .models
See Also
-
dials::grid_regular()
: For making parameter grids. -
workflowsets::workflow_set()
: For creating aworkflowset
from the.models
list stored in the ".models" column. -
modeltime_fit_workflowset()
: For fitting aworkflowset
to forecast data.
Examples
library(tidymodels)
# Parameters that get optimized
grid_tbl <- grid_regular(
learn_rate(),
levels = 3
)
# Generate model specs
grid_tbl %>%
create_model_grid(
f_model_spec = boost_tree,
engine_name = "xgboost",
# Static boost_tree() args
mode = "regression",
# Static set_engine() args
engine_params = list(
max_depth = 5
)
)