internalGetMetrics: Calculate overall performance metrics

In nbc4va: Bayes Classifier for Verbal Autopsy Data

Calculate overall performance metrics

Description

A vector providing overall performance metrics based on input predicted and observed cases.

Usage

internalGetMetrics(
  pred,
  obs,
  causes = unique(c(pred, obs)),
  csmfa.obs = NULL,
  causeMetrics = internalGetCauseMetrics(pred, obs, causes)
)

Arguments

pred	Chracter vector of predicted causes for each case.
obs	Character vector of observed causes for each case.
causes	Character vector of all possible causes including ones that are not in the pred or obs.
csmfa.obs	A character vector of the true causes for calculating the CSMF accuracy.
causeMetrics	Dataframe of a performance metrics per cause (see internalGetCauseMetrics): Columns: Cause, TruePositives, TrueNegatives, FalsePositives, FalseNegatives, PredictedFrequency, ObservedFrequency, Sensitivity, CSMFpredicted, CSMFobserved Cause (vectorof char): The unique causes from both the obs and pred inputs TruePositives (vectorof double): The total number of true positives per cause TrueNegatives (vectorof double): The total number of true negatives per cause FalsePositives (vectorof double): The total number of false positives per cause FalseNegatives (vectorof double): The total number of false negatives per cause PredictedFrequency (vectorof double): The occurence of a cause in the pred input ObservedFrequency (vectorof double): The occurence of a cause in the obs input Sensitivity (vectorof double): the sensitivity for a cause CSMFpredicted (vectorof double): the cause specific mortality fraction for a cause given the predicted deaths CSMFobserved (vectorof double): the cause specific mortality fraction for a cause given the observed deaths

Details

Developer Note: Depends on the internalGetCSMFAcc function to get the CSMF Accuracy.

Value

metrics Named numeric vector of performance metrics (see Methods documentation):

• Names: TruePositives, TrueNegatives, FalsePositives, FalseNegatives, Accuracy, Sensitivity, Specificity, PCCC, CSMFMaxError, CSMFaccuracy

• TruePositives (double): total number of true positives

• TrueNegatives (double): total number of true negatives

• FalsePositives (double): total number of false positives

• FalseNegatives (double): total number of false negatives

• Sensitivity (double): the overall sensitivity

• PCCC (double): the partial chance corrected concordance

• CSMFMaxError (double): the maximum Cause Specific Mortality Fraction Error

• CSMFaccuracy (double): the Cause Specific Mortaliy Fraction accuracy

See Also

Other internal functions: internalGetCSMFAcc(), internalGetCSMFMaxError(), internalGetCauseMetrics(), internalNBC()

Examples

library(nbc4va)
pred <- c("HIV", "Stroke", "HIV", "Stroke")
obs <- c("HIV", "HIV", "Stroke", "Stroke")
metrics <- nbc4va::internalGetMetrics(pred, obs)

nbc4va documentation built on May 10, 2022, 5:07 p.m.