The error domain can be used to determine what range of input returns outputs that are within the tolerance level defined in this subdomain and therefore can be used to optimize algorithm (domain definition).
compose_error_v1.4.2(empirical = NULL, algorithmic = NULL)
compose_error(empirical = NULL, algorithmic = NULL)
Data frame. Variables include key
and value
.
Each row is one item in the empirical error subdomain.
Data frame. Variables include key
and value
.
Each row is one item in the algorithmic subdomain.
A list of class bco.domain
empirical <- data.frame(
"key" = c("false_negative_alignment_hits", "false_discovery"),
"value" = c("<0.0010", "<0.05"),
stringsAsFactors = FALSE
)
algorithmic <- data.frame(
"key" = c("false_positive_mutation_calls", "false_discovery"),
"value" = c("<0.00005", "0.005"),
stringsAsFactors = FALSE
)
compose_error(empirical, algorithmic) %>% convert_json()
#> {
#> "empirical_error": {
#> "false_negative_alignment_hits": "<0.0010",
#> "false_discovery": "<0.05"
#> },
#> "algorithmic_error": {
#> "false_positive_mutation_calls": "<0.00005",
#> "false_discovery": "0.005"
#> }
#> }