Creates matching precision, recall, and F-beta evaluators from a single set
of options, so all three are computed with the same average, beta,
positiveLabel, and zeroDivision settings. When the same expected/
output example object is passed to all three evaluators, the underlying
confusion matrix is only computed once and shared across them.
Creates matching precision, recall, and F-beta evaluators from a single set of options, so all three are computed with the same
average,beta,positiveLabel, andzeroDivisionsettings. When the sameexpected/outputexample object is passed to all three evaluators, the underlying confusion matrix is only computed once and shared across them.