#MLNET – Write and Load models using Machine Learning .Net

	class Program
	{
	static void Main(string[] args)
	{
	var agesRangesCsv = "AgeRangeData.csv";
	var pipeline = new LearningPipeline();
	pipeline.Add(new TextLoader<AgeRangeData>(agesRangesCsv, separator: ","));
	pipeline.Add(new Dictionarizer("Label"));
	pipeline.Add(new ColumnConcatenator("Features", "AgeStart", "AgeEnd"));
	pipeline.Add(new StochasticDualCoordinateAscentClassifier());
	pipeline.Add(new PredictedLabelColumnOriginalValueConverter {PredictedLabelColumn = "PredictedLabel"});

	var model = pipeline.Train<AgeRangeData, AgeRangePrediction>();

	var modelFilePath = "AgeRangeDataModel.zip";
	model.WriteAsync(modelFilePath);
	Console.ReadLine();
	}
	}

	class Program
	{
	private static string _modelFilePath = "AgeRangeDataModel.zip";
	private static PredictionModel<AgeRangeData, AgeRangePrediction> _model;

	static void Main(string[] args)
	{
	LoadModel();
	var prediction = _model.Predict(new AgeRangeData()
	{
	AgeStart = 1,
	AgeEnd = 2
	});
	Console.WriteLine($"Predicted age range is: {prediction.PredictedLabels}");
	Console.ReadLine();
	}

	private static async void LoadModel()
	{
	_model = await PredictionModel.ReadAsync<AgeRangeData, AgeRangePrediction>(_modelFilePath);
	}
	}

26 comments