runWorkflow: Run a workflow on a predictive task

In ltorgo/performanceEstimation: An Infra-Structure for Performance Estimation of Predictive Models

Description

This function can be used to apply (run) a workflow.

It receives in the first argument an object of class Workflow and then any other arguments that are required to run the workflow, which will typically involve at least a formula, a training data set (a data frame), and a test data set (another data frame).

Usage

runWorkflow(l, ...)

Arguments

l	An object of class Workflow
...	Further arguments that are required by the workflow function

Value

The execution of a workflow should produce a list as result. If you plan to apply any of the functions provided in this package to calculate standard performance metrics (classificationMetrics or regressionMetrics) then your list should contain at least two components: one named trues with the true values of the target variable in the test set, and the other named preds with the respective predictions of the workflow.

Author(s)

Luis Torgo [e-mail]

References

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

See Also

Workflow

Examples

## Not run: 
## A simple example
data(iris)
w1 <- Workflow("mySolution",par1="gaussian",k=10)
runWorkflow(w1,Species ~ .,iris[1:100,],iris[101:150,])

## End(Not run)

ltorgo/performanceEstimation documentation built on May 21, 2019, 8:41 a.m.