public void TrainOneVersusAll()
{
string dataPath = GetDataPath("iris.txt");
var pipeline = new Legacy.LearningPipeline(seed: 1, conc: 1);
pipeline.Add(new TextLoader(dataPath).CreateFrom <IrisData>(useHeader: false));
pipeline.Add(new ColumnConcatenator(outputColumn: "Features",
"SepalLength", "SepalWidth", "PetalLength", "PetalWidth"));
pipeline.Add(OneVersusAll.With(new StochasticDualCoordinateAscentBinaryClassifier()));
var model = pipeline.Train <IrisData, IrisPrediction>();
var testData = new TextLoader(dataPath).CreateFrom <IrisData>(useHeader: false);
var evaluator = new ClassificationEvaluator();
ClassificationMetrics metrics = evaluator.Evaluate(model, testData);
CheckMetrics(metrics);
var trainTest = new TrainTestEvaluator()
{
Kind = MacroUtilsTrainerKinds.SignatureMultiClassClassifierTrainer
}.TrainTestEvaluate <IrisData, IrisPrediction>(pipeline, testData);
CheckMetrics(trainTest.ClassificationMetrics);
}
void Metacomponents()
{
var dataPath = GetDataPath(IrisDataPath);
var pipeline = new LearningPipeline(seed: 1, conc: 1);
pipeline.Add(new TextLoader(dataPath).CreateFrom <IrisData>(useHeader: false));
pipeline.Add(new Dictionarizer(new[] { "Label" }));
pipeline.Add(new ColumnConcatenator(outputColumn: "Features",
"SepalLength", "SepalWidth", "PetalLength", "PetalWidth"));
// This will throw exception during training time if you specify any other than binary classifier.
pipeline.Add(OneVersusAll.With(new StochasticDualCoordinateAscentBinaryClassifier()));
var model = pipeline.Train <IrisData, IrisPrediction>();
var testData = new TextLoader(dataPath).CreateFrom <IrisData>(useHeader: false);
var evaluator = new ClassificationEvaluator();
ClassificationMetrics metrics = evaluator.Evaluate(model, testData);
var prediction = model.Predict(new IrisData {
PetalLength = 1, PetalWidth = 2, SepalLength = 1.4f, SepalWidth = 1.6f
});
}
