public void TestSmallSample2Fold()
{
var stratifiedKFoldCrossValidation =
new StratifiedKFoldCrossValidation <string>(smallSample, 2, 1);
string[] expected3 = { "7", "9", "5", "2", "10", "20", "26", "16", "22", "14", "27", "25", "28", "29", "11" };
Assert.AreEqual(expected3, stratifiedKFoldCrossValidation.GetTestFold(0).ToArray());
}
public void TestSmallSample5Fold()
{
var stratifiedKFoldCrossValidation =
new StratifiedKFoldCrossValidation <string>(smallSample, 5, 1);
string[] expected2 = { "7", "9", "20", "26", "16", "22" };
Assert.AreEqual(expected2, stratifiedKFoldCrossValidation.GetTestFold(0).ToArray());
}
/**
* <summary> Execute Stratified Single K-fold cross-validation with the given classifier on the given data set using the given parameters.</summary>
*
* <param name="experiment">Experiment to be run.</param>
* <returns>A Performance instance.</returns>
*/
public Performance.Performance Execute(Experiment experiment)
{
var crossValidation =
new StratifiedKFoldCrossValidation <Instance.Instance>(experiment.GetDataSet().GetClassInstances(), _k,
experiment.GetParameter().GetSeed());
var trainSet = new InstanceList.InstanceList(crossValidation.GetTrainFold(0));
var testSet = new InstanceList.InstanceList(crossValidation.GetTestFold(0));
return(experiment.GetClassifier().SingleRun(experiment.GetParameter(), trainSet, testSet));
}
/**
* <summary> Execute Stratified K-fold cross-validation with the given classifier on the given data set using the given parameters.</summary>
*
* <param name="experiment">Experiment to be run.</param>
* <returns>An ExperimentPerformance instance.</returns>
*/
public override ExperimentPerformance Execute(Experiment experiment)
{
var result = new ExperimentPerformance();
var crossValidation =
new StratifiedKFoldCrossValidation <Instance.Instance>(experiment.GetDataSet().GetClassInstances(), K,
experiment.GetParameter().GetSeed());
RunExperiment(experiment.GetClassifier(), experiment.GetParameter(), result, crossValidation);
return(result);
}
/**
* <summary> Execute Stratified K-fold cross-validation with the given classifier on the given data set using the given parameters.</summary>
*
* <param name="experiment">Experiment to be run.</param>
* <returns>An ExperimentPerformance instance.</returns>
*/
public override ExperimentPerformance Execute(Experiment experiment)
{
var result = new ExperimentPerformance();
var instanceList = experiment.GetDataSet().GetInstanceList();
var partition = instanceList.Partition(0.25, new Random(experiment.GetParameter().GetSeed()));
var crossValidation =
new StratifiedKFoldCrossValidation <Instance.Instance>(partition.Get(1).DivideIntoClasses().GetLists(),
K, experiment.GetParameter().GetSeed());
RunExperiment(experiment.GetClassifier(), experiment.GetParameter(), result, crossValidation,
partition.Get(0));
return(result);
}
public void TestLargeSample10Fold()
{
var stratifiedKFoldCrossValidation =
new StratifiedKFoldCrossValidation <int>(largeSample, 10, 1);
for (var i = 0; i < 10; i++)
{
var items = new HashSet <int>();
var trainFold = stratifiedKFoldCrossValidation.GetTrainFold(i);
var testFold = stratifiedKFoldCrossValidation.GetTestFold(i);
items.UnionWith(trainFold);
items.UnionWith(testFold);
Assert.AreEqual(900, testFold.Count);
Assert.AreEqual(8100, trainFold.Count);
Assert.AreEqual(9000, items.Count);
var trainCounts = new int[3];
foreach (var integer in trainFold)
{
if (integer < 1000)
{
trainCounts[0]++;
}
else
{
if (integer < 4000)
{
trainCounts[1]++;
}
else
{
trainCounts[2]++;
}
}
}
Assert.AreEqual(900, trainCounts[0]);
Assert.AreEqual(2700, trainCounts[1]);
Assert.AreEqual(4500, trainCounts[2]);
var testCounts = new int[3];
foreach (var integer in testFold)
{
if (integer < 1000)
{
testCounts[0]++;
}
else
{
if (integer < 4000)
{
testCounts[1]++;
}
else
{
testCounts[2]++;
}
}
}
Assert.AreEqual(100, testCounts[0]);
Assert.AreEqual(300, testCounts[1]);
Assert.AreEqual(500, testCounts[2]);
}
}