mikropml (version 1.7.0)

calc_baseline_precision: Calculate the fraction of positives, i.e. baseline precision for a PRC curve

Description

Calculate the fraction of positives, i.e. baseline precision for a PRC curve

Usage

calc_baseline_precision(dataset, outcome_colname = NULL, pos_outcome = NULL)

Value

the baseline precision based on the fraction of positives

Arguments

dataset

Data frame with an outcome variable and other columns as features. Alternatively, the input can be in TreeSummarizedExperiment format.

outcome_colname

Column name as a string of the outcome variable (default NULL; the first column will be chosen automatically).

pos_outcome

the positive outcome from outcome_colname, e.g. "cancer" for the otu_mini_bin dataset.

Author

Kelly Sovacool,

Examples

# calculate the baseline precision
data.frame(y = c("a", "b", "a", "b")) %>%
  calc_baseline_precision(
    outcome_colname = "y",
    pos_outcome = "a"
  )


calc_baseline_precision(otu_mini_bin,
  outcome_colname = "dx",
  pos_outcome = "cancer"
)


# if you're not sure which outcome was used as the 'positive' outcome during
# model training, you can access it from the trained model and pass it along:
calc_baseline_precision(otu_mini_bin,
  outcome_colname = "dx",
  pos_outcome = otu_mini_bin_results_glmnet$trained_model$levels[1]
)