public void Predict_PredictionRequestWithoutParameters_Null()
{
var predictor = new SearchBasedPredictor(null);
var model = (HiddenMarkovModelMixtureDistribution)HiddenMarkovModelFactory.GetModel(new ModelCreationParameters <Mixture <IMultivariateDistribution> >()
{
NumberOfComponents = _NumberOfComponents, NumberOfStates = _NumberOfStates
});
var request = new SearchBasedPredictionRequest();
var value = predictor.Predict(model, request);
Assert.IsNull(value);
}
public void Predict_PredictionRequestWihtoutNumberOfSamplePoints_Null()
{
var predictor = new SearchBasedPredictor(null);
var model = (HiddenMarkovModelMixtureDistribution)HiddenMarkovModelFactory.GetModel(new ModelCreationParameters <Mixture <IMultivariateDistribution> >()
{
NumberOfComponents = _NumberOfComponents, NumberOfStates = _NumberOfStates
});
var request = new SearchBasedPredictionRequest();
request.AlgorithmSpecificParameters = new Dictionary <string, string>();
var value = predictor.Predict(model, request);
Assert.IsNull(value);
}
public void Predict_ModelAndPredictionRequest_PredictedValue()
{
var util = new TestDataUtils();
var series = util.GetSvcData(util.FTSEFilePath, new DateTime(2010, 12, 18), new DateTime(2011, 12, 18));
var model = (HiddenMarkovModelMixtureDistribution)HiddenMarkovModelFactory.GetModel(new ModelCreationParameters <Mixture <IMultivariateDistribution> >()
{
NumberOfComponents = _NumberOfComponents, NumberOfStates = _NumberOfStates
});
model.Normalized = true;
model.Train(series, _NumberOfIterations, _LikelihoodTolerance);
var request = new SearchBasedPredictionRequest();
request.TrainingSet = series;
request.NumberOfDays = 1;
var predictor = new SearchBasedPredictor(null);
var value = predictor.Predict(model, request);
Assert.AreEqual(0, value);
}