errorMeasures: Calculate Error Measures
Description
Computes various error measures for the classification of a data set.Usage
errorMeasures(result)
Value
- A list with components
alpha, beta, accuracy,
precision, sensitivity and specificity, each a number in
the range $[0,1]$.
Details
The true matching status must be known for all record pairs in result,
i. e. there must be no other values than 0 or 1 in
result$pairs$is_match.
Let $\mathit{TP}$ be the number of correctly classified matches
(true positives), $\mathit{TN}$ the number of correctly classified
non-matches (true negatives), $\mathit{FP}$ and $\mathit{FN}$
the number of misclassified non-matches and matches
(false positives and false negatives). The calculated error measures are:
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]