Get sufficient explanations for a prediction

Usage

bfs_sfx(predict_f, evidence, outcome, expected)

Arguments

predict_f: A function that takes in a dataframe of evidence and outputs a list with the prediction for each row.
evidence: A dataframe of one row where all columns are of type factor.
outcome: The resulting prediction for the evidence.
expected: The expected prediction of the evidence

Value

Sufficient explanations as a list of named lists.

Examples

set.seed(40)
download.file("https://www.bnlearn.com/bnrepository/child/child.rda",
  "child.rda", "auto",
  quiet = TRUE
)
load("child.rda") # Load CHILD Bayesian Network
evidence <- data.frame(
  LVHReport = factor(x = "yes", levels = dimnames(bn$LVHreport$prob)[[1]]),
  LowerBodyO2 = factor(x = "5-12", levels = dimnames(bn$LowerBodyO2$prob)[[1]]),
  CO2Report = factor(x = "<7.5", levels = dimnames(bn$CO2Report$prob)[[1]]),
  XrayReport = factor(x = "Oligaemic", levels = dimnames(bn$XrayReport$prob)[[1]])
)
outcome <- predict(
  object = bn, node = bn$Disease$node, data = evidence,
  method = "bayes-lw"
)
print(paste("Outcome: ", outcome))
#> [1] "Outcome:  Fallot"
expected <- factor("TGA", levels = levels(outcome))
predict_f <- function(df) {
  predict(object = bn, node = bn$Disease$node, data = df, method = "bayes-lw")
}
print(bfs_sfx(predict_f, evidence, outcome, expected))
#> [[1]]
#> [[1]]$LVHReport
#> [1] yes
#> Levels: yes no
#> 
#> [[1]]$XrayReport
#> [1] Oligaemic
#> Levels: Normal Oligaemic Plethoric Grd_Glass Asy/Patchy
#> 
#>