getFoldsResults: Obtain the results on each iteration of a learner

Description

This function allows you to obtain the scores obtained by a learner on the different iterations that form an experimental comparison. These scores are obtained for a particular data set of this comparison.

Usage

getFoldsResults(results,learner,dataSet)

Arguments

results

This is a compExp object (type "class?compExp" for details) that contains the results of an experimental comparison obtained through the experimentalComparison() function.

learner

This is the string that identifies the learner.

dataSet

The string that identifies the data set for which you want to get the scores.

Value

The result of the function is a matrix with as many columns as there are evaluation statistics in the experimental comparison, and with as many rows as there are iterations in this experiment. The values on this matrix are the scores of the learner for respective statistic on the different iterations of the process.

References

Torgo, L. (2010) Data Mining using R: learning with case studies, CRC Press (ISBN: 9781439810187).

http://www.dcc.fc.up.pt/~ltorgo/DataMiningWithR

Examples

Run this code

## Estimating several evaluation metrics on different variants of a
## regression tree on  a data set, using one repetition of 10-fold CV
data(swiss)

## First the user defined functions 
cv.rpartXse <- function(form, train, test, ...) {
    require(DMwR)
    t <- rpartXse(form, train, ...)
    p <- predict(t, test)
    mse <- mean((p - resp(form, test))^2)
    c(nmse = mse/mean((mean(resp(form, train)) - resp(form, test))^2), 
        mse = mse)
}

results <- experimentalComparison(
               c(dataset(Infant.Mortality ~ ., swiss)),
               c(variants('cv.rpartXse',se=c(0,0.5,1))),
               cvSettings(1,10,1234)
                                 )

## Get the scores of a specific learner
getFoldsResults(results,'cv.rpartXse.v1','swiss')

## Get the scores of the learner that obtained the best NMSE on the
## swiss data set
getFoldsResults(results,bestScores(results)$swiss['nmse','system'],'swiss')