R: Calculate Error Measures

getErrorMeasures-methods {RecordLinkage} | R Documentation

## Calculate Error Measures

### Description

Computes various error measures for the classification of a data set.

### Details

Let TP be the number of correctly classified matches (true positives), TN the number of correctly classified non-matches (true negatives), FP and FN the number of misclassified non-matches and matches (false positives and false negatives). The calculated error measures are:

alpha error

  FN/(TP+FN)

beta error

  FP/(TN+FP)

accuracy

  (TP+TN)/(TP+TN+FP+FN)

precision

  TP/(TP+FP)

sensitivity

  TP/(TP+FN)

specificity

  TN/(TN+FP)

ppv

  Positive predictive value:TP/(TP+FP)

npv

  Negative predictive value:TN/(TN+FN)

### Value

A list with components `alpha`, `beta`, `accuracy`, `precision`, `sensitivity`, `specificity`, `ppv` and `npv`, each a number in the range [0,1].

### Methods

`signature(object = "RecLinkResult")`

  Method for S3 result objects of class `"RecLinkResult"`

`signature(object = "RLResult")`

  Method for S4 objects of class `"RLResult"`, from classification of big data objects (see `"RLBigData"`, `"RLBigDataDedup"`, `"RLBigDataLinkage"`)

A wrapper function `errorMeasures(result)` exists for compatibility with package version 0.2.

### Note

Record pairs with unknown true matching status (e.g. due to missing values in the argument `identity` to `RLBigDataDedup`) and possible links are not counted, which can distort the values returned by this function.

### Author(s)

Murat Sariyar, Andreas Borg

[Package RecordLinkage version 0.4-11.2 Index]