public static async Task <PredictionModel <TaxiTrip, TaxiTripFarePrediction> > TrainModel()
{
var pipeline = new LearningPipeline();
var loadData = new TextLoader(_dataPath).CreateFrom <TaxiTrip>(useHeader: true, separator: ',');
var copyLabels = new ColumnCopier(("FareAmount", "Label"));
var convertToNumeric = new CategoricalOneHotVectorizer("VendorId", "RateCode", "PaymentType");
var features = new ColumnConcatenator("Features",
"VendorId", "RateCode", "PassengerCount", "TripDistance", "PaymentType");
pipeline.Add(loadData);
pipeline.Add(copyLabels);
pipeline.Add(convertToNumeric);
pipeline.Add(features);
pipeline.Add(new FastTreeRegressor());
var model = pipeline.Train <TaxiTrip, TaxiTripFarePrediction>();
await model.WriteAsync(_modelPath);
return(model);
}
public void KeyToVectorWithBagTest()
{
string dataPath = GetDataPath(@"breast-cancer.txt");
var pipeline = new Legacy.LearningPipeline();
pipeline.Add(new Legacy.Data.TextLoader(dataPath)
{
Arguments = new TextLoaderArguments
{
Separator = new[] { '\t' },
HasHeader = true,
Column = new[]
{
new TextLoaderColumn()
{
Name = "Label",
Source = new [] { new TextLoaderRange(0) },
Type = Legacy.Data.DataKind.Num
},
new TextLoaderColumn()
{
Name = "F1",
Source = new [] { new TextLoaderRange(1, 1) },
Type = Legacy.Data.DataKind.Num
},
new TextLoaderColumn()
{
Name = "F2",
Source = new [] { new TextLoaderRange(2, 2) },
Type = Legacy.Data.DataKind.TX
}
}
}
});
var vectorizer = new CategoricalOneHotVectorizer();
var categoricalColumn = new CategoricalTransformColumn()
{
OutputKind = CategoricalTransformOutputKind.Bag, Name = "F2", Source = "F2"
};
vectorizer.Column = new CategoricalTransformColumn[1] {
categoricalColumn
};
pipeline.Add(vectorizer);
pipeline.Add(new ColumnConcatenator("Features", "F1", "F2"));
pipeline.Add(new FastTreeBinaryClassifier()
{
NumLeaves = 2, NumTrees = 1, MinDocumentsInLeafs = 2
});
var model = pipeline.Train <BreastCancerData, BreastCancerPrediction>();
var subDir = Path.Combine("..", "..", "BaselineOutput", "Common", "Onnx", "BinaryClassification", "BreastCancer");
var onnxPath = GetOutputPath(subDir, "KeyToVectorBag.onnx");
DeleteOutputPath(onnxPath);
var onnxAsJsonPath = GetOutputPath(subDir, "KeyToVectorBag.json");
DeleteOutputPath(onnxAsJsonPath);
OnnxConverter converter = new OnnxConverter()
{
InputsToDrop = new[] { "Label" },
OutputsToDrop = new[] { "Label", "F1", "F2", "Features" },
Onnx = onnxPath,
Json = onnxAsJsonPath,
Domain = "Onnx"
};
converter.Convert(model);
// Strip the version.
var fileText = File.ReadAllText(onnxAsJsonPath);
fileText = Regex.Replace(fileText, "\"producerVersion\": \"([^\"]+)\"", "\"producerVersion\": \"##VERSION##\"");
File.WriteAllText(onnxAsJsonPath, fileText);
CheckEquality(subDir, "KeyToVectorBag.json");
Done();
}