View source: R/filter_parameters.R
filter_parameters | R Documentation |
For objects produced by the tune_*()
functions, there may only be a subset
of tuning parameter combinations of interest. For large data sets, it might be
helpful to be able to remove some results. This function trims the .metrics
column of unwanted results as well as columns .predictions
and .extracts
(if they were requested).
filter_parameters(x, ..., parameters = NULL)
x |
An object of class |
... |
Expressions that return a logical value, and are defined in terms
of the tuning parameter values. If multiple expressions are included, they
are combined with the |
parameters |
A tibble of tuning parameter values that can be used to
filter the predicted values before processing. This tibble should only have
columns for tuning parameter identifiers (e.g. |
Removing some parameter combinations might affect the results of autoplot()
for the object.
A version of x
where the lists columns only retain the parameter
combinations in parameters
or satisfied by the filtering logic.
library(dplyr)
library(tibble)
# For grid search:
data("example_ames_knn")
## -----------------------------------------------------------------------------
# select all combinations using the 'rank' weighting scheme
ames_grid_search %>%
collect_metrics()
filter_parameters(ames_grid_search, weight_func == "rank") %>%
collect_metrics()
rank_only <- tibble::tibble(weight_func = "rank")
filter_parameters(ames_grid_search, parameters = rank_only) %>%
collect_metrics()
## -----------------------------------------------------------------------------
# Keep only the results from the numerically best combination
ames_iter_search %>%
collect_metrics()
best_param <- select_best(ames_iter_search, metric = "rmse")
ames_iter_search %>%
filter_parameters(parameters = best_param) %>%
collect_metrics()
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