public void ModelTrainingConverges()
{
ImageData img = ResourceManager.UsingDebugBitmap("testgrid1px.png", (bmp) => {
return ImageData.FromImage(bmp);
});
Label[,] labels = new Label[img.XSites,img.YSites];
Classification cfc = new Classification(labels);
ModelBuilder mbr = new ModelBuilder(ConcatenateFeatures.INSTANCE, LinearBasis.INSTANCE, 1d, 3000, 1d, 1d);
Model mfm = mbr.PseudoLikelihoodTrain("","", new ImageData[1]{img},new Classification[1]{cfc});
Assert.AreNotEqual(mfm.TimeToConverge, mbr.MaxIters);
}
public void CanClassify()
{
ImageData img = ResourceManager.UsingDebugBitmap("testgrid1px.png", (bmp) => {
return ImageData.FromImage(bmp);
});
Label[,] labels = new Label[img.XSites,img.YSites];
Classification cfc = new Classification(labels);
ModelBuilder mbr = new ModelBuilder(ConcatenateFeatures.INSTANCE, LinearBasis.INSTANCE, 1d, 3000, 1d, 1d);
Model mfm = mbr.PseudoLikelihoodTrain("", "", new ImageData[1]{img},new Classification[1]{cfc});
Classification inferred = mfm.MaximumAPosterioriInfer(img);
Assert.IsNotNull(inferred);
}