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); }