R: Classify record pairs with EpiLink weights

epiClassify {RecordLinkage} | R Documentation

## Classify record pairs with EpiLink weights

### Description

Classifies record pairs as link, non-link or possible link based on weights computed by `epiWeights` and the thresholds passed as arguments.

### Usage

    epiClassify(rpairs, threshold.upper, threshold.lower = threshold.upper,
      ...)

    ## S4 method for signature 'RecLinkData'
    epiClassify(rpairs, threshold.upper, threshold.lower = threshold.upper)

    ## S4 method for signature 'RLBigData'
    epiClassify(rpairs, threshold.upper, threshold.lower = threshold.upper,
      e = 0.01, f = getFrequencies(rpairs), withProgressBar = (sink.number()==0))

### Arguments

`rpairs` | `RecLinkData` object. Record pairs to be classified.
`threshold.upper` | A numeric value between 0 and 1.
`threshold.lower` | A numeric value between 0 and 1 lower than `threshold.upper`
`e` | Numeric vector. Estimated error rate(s).
`f` | Numeric vector. Average frequency of attribute values.
`withProgressBar` | Logical. Whether to display a progress bar.
`...` | Placeholder for optional arguments

### Details

All record pairs with weights greater or equal `threshold.upper` are classified as links. Record pairs with weights smaller than `threshold.upper` and greater or equal `threshold.lower` are classified as possible links. All remaining records are classified as non-links.

For the `"RecLinkData"` method, weights must have been calculated for `rpairs` using `epiWeights`.

A progress bar is displayed by the `"RLBigData"` method only if weights are calculated on the fly and, by default, unless output is diverted by `sink` (e.g. in a Sweave script).

### Value

For the `"RecLinkData"` method, a S3 object of class `"RecLinkResult"` that represents a copy of `newdata` with element `rpairs$prediction`, which stores the classification result, as addendum.

For the `"RLBigData"` method, a S4 object of class `"RLResult"`.

### Author(s)

Andreas Borg, Murat Sariyar

### See Also

`epiWeights`

### Examples

    # generate record pairs
    data(RLdata500)
    p=compare.dedup(RLdata500,strcmp=TRUE ,strcmpfun=levenshteinSim,
      identity=identity.RLdata500, blockfld=list("by", "bm", "bd"))

    # calculate weights
    p=epiWeights(p)

    # classify and show results
    summary(epiClassify(p,0.6))

[Package RecordLinkage version 0.4-11.2 Index]