public void TestTrainValidData()
{
List <List <object> > validData = new List <List <object> >();
for (int i = 0; i < 5; i++)
{
validData.Add(GenerateValidList(5));
}
List <object> validTargetData = GenerateValidTargetData(5);
KnnModel.Train(validData, validTargetData);
}
public void KNN_Test()
{
Logger.Info("KNN_Test");
var problem = ProblemFactory.CreateClassificationProblem(ClassificationProblemType.ChessBoard);
Logger.Info("Loading training data.");
var tSet = problem.TrainingSet;
var vSet = problem.ValidationSet;
var classifier = new KNN
{
KNN_K = 7,
TrainSet = tSet
};
classifier.Train();
Logger.Info("Doing cross-validation.");
var hit = (from e in vSet.Examples let iResult = classifier.Predict(e.X) where e.Label.Id == iResult select e).Count();
var correctRatio = 1.0 * hit / vSet.Count;
Logger.Info("CorrectRatio: {0}", correctRatio);
Assert.IsTrue(correctRatio > 0.900, string.Format("KNN (2-class) Correct Ratio, expected: greater than 0.900, actual: {0}.", correctRatio));
}
public bool Train(List <List <object> > X, List <object> Y)
{
try
{
Model.Train(X, Y);
} catch (InvalidDataFormatException)
{
return(false);
}
return(true);
}
