View source: R/apply_methods.R
apply_methods | R Documentation |
apply_methods() and its aliases apply_metrics and begin_benchmark take either lists of datasets or benchmark_tbl objects and applies a list of functions. The output is a benchmark_tbl where each method has been applied to each dataset or preceeding result.
apply_methods(x, fn_list, name = NULL, suppress.messages = TRUE)
## S3 method for class 'list'
apply_methods(x, fn_list, name = NULL, suppress.messages = TRUE)
## S3 method for class 'benchmark_tbl'
apply_methods(x, fn_list, name = NULL, suppress.messages = TRUE)
## S3 method for class 'tbl_df'
apply_methods(x, fn_list, name = NULL, suppress.messages = TRUE)
apply_metrics(x, fn_list, name = NULL, suppress.messages = TRUE)
begin_benchmark(x, fn_list, name = NULL, suppress.messages = TRUE)
x |
the list of data or benchmark tibble to apply methods to |
fn_list |
the list of methods to be applied |
name |
(optional) the name of the column for methods applied |
suppress.messages |
TRUE if messages from running methods should be suppressed |
benchmark_tbl object containing results from methods applied, the first column is the name of the dataset as factors, middle columns contain method names as factors and the final column is a list of results of applying the methods.
time_methods
# list of data
datasets <- list(
set1 = rnorm(500, mean = 2, sd = 1),
set2 = rnorm(500, mean = 1, sd = 2)
)
# list of functions
add_noise <- list(
none = identity,
add_bias = function(x) { x + 1 }
)
res <- apply_methods(datasets, add_noise)
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