topPerformer: Obtain the workflow that best performed in terms of a metric...
In performanceEstimation: An Infra-Structure for Performance Estimation of Predictive Models

Description Usage Arguments Details Value Author(s) References See Also Examples

This function can be used to obtain the workflow (an object of class Workflow) that performed better in terms of a given metric on a certain task.

1	topPerformer(compRes,metric,task,max=FALSE,stat="avg")

`compRes`	A `ComparisonResults` object with the results of your experimental comparison.
`metric`	A string with the name of a metric estimated in the comparison
`task`	A string with the name of a predictive task used in the comparison
`max`	A boolean (defaulting to `FALSE`) indicating the meaning of best performance for the selected metric. If this is `FALSE` it means that the goal is to minimize this metric, otherwise it means that the metric is to be maximized.
`stat`	The statistic to be used to obtain the ranks. The options are the statistics produced by the function `summary` applied to objects of class `ComparisonResults`, i.e. "avg", "std", "med", "iqr", "min", "max" or "invalid" (defaults to "avg").

This is an utility function that can be used to obtain the workflow (an object of class Workflow) that achieved the best performance on a given predictive task in terms of a certain evaluation metric. The notion of best performance depends on the type of evaluation metric, thus the need for the max argument. Some evaluation statistics are to be maximized (e.g. accuracy), while others are to be minimized (e.g. mean squared error). For the former you should use max=TRUE, while the latter require max=FALSE (the default).

The function returns an object of class Workflow .

Luis Torgo ltorgo@dcc.fc.up.pt

Torgo, L. (2014) An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in R. arXiv:1412.0436 [cs.MS] http://arxiv.org/abs/1412.0436

performanceEstimation, topPerformers, rankWorkflows, metricsSummary

## Not run: 
## Estimating several evaluation metrics on different variants of a
## regression tree and of a SVM, on  two data sets, using one repetition
## of  10-fold CV

data(swiss)
data(mtcars)
library(e1071)

## run the experimental comparison
results <- performanceEstimation(
               c(PredTask(Infant.Mortality ~ ., swiss),
                 PredTask(mpg ~ ., mtcars)),
               c(workflowVariants(learner='svm',
                                  learner.pars=list(cost=c(1,5),gamma=c(0.1,0.01))
                                 )
               ),
               EstimationTask(metrics=c("mse","mae"),method=CV(nReps=2,nFolds=5))
                                 )

## get the top performer workflow for a metric and task
topPerformer(results,"mse","swiss.Infant.Mortality")

## End(Not run)