doctor.validate: Validates a model using validaing samples.

In FeaLect: Scores Features for Feature Selection

Description

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.

Usage

doctor.validate(true.labels, predictions)

Arguments

true.labels	A vector of 0 and 1.
predictions	A vector of 0 and 1.

Details

F-measure is equal to: 2 times precision times recall / (precision+recall).

Value

F-measure, precision, and recall are calculated. Also, the mis-labelled cases are reported.

Author(s)

Habil Zare

References

"Statistical Analysis of Overfitting Features", manuscript in preparation.

See Also

FeaLect, train.doctor, doctor.validate, random.subset, compute.balanced,compute.logistic.score, ignore.redundant, input.check.FeaLect

Examples

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)

FeaLect documentation built on May 30, 2017, 7:20 a.m.

Fits a logistic regression model using the linear scores

FeaLect index

Computes the scores of the features.