Ejemplo n.º 1
0
        public void TestEntryPointXGBoostBinary()
        {
            var env  = EnvHelper.NewTestEnvironment(conc: 1);
            var iris = FileHelper.GetTestFile("iris_binary.txt");
            var df   = DataFrame.ReadCsv(iris, sep: '\t', dtypes: new DataKind?[] { DataKind.R4 });

            var importData       = df.EPTextLoader(iris, sep: '\t', header: true);
            var learningPipeline = new GenericLearningPipeline(conc: 1);

            learningPipeline.Add(importData);
            learningPipeline.Add(new ColumnConcatenator("Features", "Sepal_length", "Sepal_width"));
            learningPipeline.Add(new Scikit.ML.XGBoostWrapper.XGBoostBinary());
            // Fails here due to missing variable.
            return;

            var predictor   = learningPipeline.Train();
            var predictions = predictor.Predict(df);
            var dfout       = DataFrame.ReadView(predictions);

            Assert.AreEqual(dfout.Shape, new Tuple <int, int>(150, 9));
        }
Ejemplo n.º 2
0
        public void TestXGBoostMultiClassification()
        {
            var methodName   = string.Format("{0}", System.Reflection.MethodBase.GetCurrentMethod().Name);
            var dataFilePath = FileHelper.GetTestFile("iris.txt");

            var outData  = FileHelper.GetOutputFile("outData1.txt", methodName);
            var outData2 = FileHelper.GetOutputFile("outData2.txt", methodName);

            var env    = EnvHelper.NewTestEnvironment();
            var loader = env.CreateLoader("Text{col=Label:R4:0 col=Features:R4:1-4 header=+}",
                                          new MultiFileSource(dataFilePath));

            var            roles   = env.CreateExamples(loader, "Features", "Label");
            var            trainer = EnvHelper.CreateTrainer <XGBoostMulticlassTrainer>(env, "exgbmc{iter=10}");
            IDataTransform pred    = null;

            using (var ch = env.Start("Train"))
            {
                var model = trainer.Train(new TrainContext(roles));
                pred = ScoreUtils.GetScorer(model, roles, env, roles.Schema);
            }

            var outputDataFilePath = FileHelper.GetOutputFile("outputDataFilePath.txt", methodName);

            EnvHelper.SavePredictions(env, pred, outputDataFilePath);
            Assert.IsTrue(File.Exists(outputDataFilePath));

            var outModelFilePath = FileHelper.GetOutputFile("outModelFilePath.zip", methodName);

            EnvHelper.SaveModel(env, pred, outModelFilePath);
            Assert.IsTrue(File.Exists(outModelFilePath));

            var d1 = File.ReadAllText(outputDataFilePath);

            Assert.IsTrue(d1.Length > 0);
        }