Generates training data by unsupervised classification.
genSamples(dataset, num.non, des.mprop = 0.1)Object of class RecLinkData. Data pairs from
which to sample.
Positive Integer. Number of desired non-links in the training set.
Real number in the range [0,1]. Ratio of number of links to number of non-links in the training set.
A list of "RecLinkResult" objects.
The sampled training data.
All other record pairs
The application of supervised classifiers (via classifySupv)
requires a training set of record pairs with known matching status.
Where no such data are available, genSamples can be used to generate
training data. The matching status is determined by unsupervised
clustering with bclust. Subsequently, the desired number of
links and non-links are sampled.
If the requested numbers of matches or non-matches is not feasible, a warning is issued and the maximum possible number is considered.
splitData for splitting data sets without clustering.