Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/doctor.validate.R
A model fitted on the training samples, can be validated on a separate validating set. The recall, precision, and accuracy of the model are computed.
1 | doctor.validate(true.labels, predictions)
|
true.labels |
A vector of 0 and 1. |
predictions |
A vector of 0 and 1. |
F-measure is equal to: 2 times precision times recall / (precision+recall).
F-measure, precision, and recall are calculated. Also, the mis-labeled cases are reported.
Habil Zare
"Statistical Analysis of Overfitting Features", manuscript in preparation.
FeaLect
, train.doctor
, doctor.validate
,
random.subset
, compute.balanced
,compute.logistic.score
,
ignore.redundant
, input.check.FeaLect
1 2 3 4 5 | tls <- c(1,1,1,0,0)
ps <- c(1,1,0,1,0)
names(tls) <- 1:5; names(ps) <- 1:5
doctor.validate(true.labels=tls, predictions=ps)
|
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