public ITransformer TrainModel(TrainingAlgorithm algorithm, DataControl.TrainingOptions options)
{
switch (algorithm)
{
case TrainingAlgorithm.LOGISTIC_REGRESSION:
return(LogisticRegression(options));
case TrainingAlgorithm.NAIVE_BAYES:
return(NaiveBayes(options));
case TrainingAlgorithm.BINARY_STOCHASTIC_DUAL_COORDINATE_ASCENT:
return(BinaryStochasticDualCoordinateAscent(options));
case TrainingAlgorithm.FAST_TREE:
return(FastTree(options));
case TrainingAlgorithm.STOCHASTIC_DUAL_COORDINATE_ASCENT:
return(StochasticDualCoordinateAscent(options));
case TrainingAlgorithm.STOCHASTIC_GRADIENT_DESCENT:
return(StochasticGradientDescent(options));
default:
return(null);
}
}
private ITransformer LogisticRegression(DataControl.TrainingOptions options)
{
var pipeline = context.Transforms.Conversion
.ConvertType(options.LabelColumn, options.LabelColumn, DataKind.R4)
.Append(context.MulticlassClassification.Trainers.LogisticRegression(
labelColumn: options.LabelColumn,
featureColumn: options.FeatureColumn));
Console.WriteLine("============== Create and Train Logistic Regression Model ==============");
var model = pipeline.Fit(trainData);
Console.WriteLine("================= Finished Training ================");
Console.WriteLine();
return(model);
}
private ITransformer FastTree(DataControl.TrainingOptions options)
{
var pipeline = context.BinaryClassification.Trainers.FastTree(
labelColumn: options.LabelColumn,
featureColumn: options.FeatureColumn,
learningRate: options.LearningRate
);
Console.WriteLine("============== Create and Train Averaged Perceptron Model ==============");
var model = pipeline.Fit(trainData);
Console.WriteLine("================= Finished Training ================");
Console.WriteLine();
return(model);
}
private ITransformer BinaryStochasticDualCoordinateAscent(DataControl.TrainingOptions options)
{
var pipeline = context.BinaryClassification.Trainers.StochasticDualCoordinateAscent(
labelColumn: options.LabelColumn,
featureColumn: options.FeatureColumn,
maxIterations: options.MaxIterations
);
Console.WriteLine("============== Create and Train Averaged Perceptron Model ==============");
var model = pipeline.Fit(trainData);
Console.WriteLine("================= Finished Training ================");
Console.WriteLine();
return(model);
}
private ITransformer StochasticDualCoordinateAscent(DataControl.TrainingOptions options)
{
var pipeline = context.Transforms.Conversion
.ConvertType(options.LabelColumn, options.LabelColumn, DataKind.R4)
.Append(context.MulticlassClassification.Trainers.StochasticDualCoordinateAscent(
labelColumn: options.LabelColumn,
featureColumn: options.FeatureColumn,
maxIterations: options.MaxIterations));
Console.WriteLine("========== Training Stochastic Dual Coordinate Ascent Model =========");
var model = pipeline.Fit(trainData);
Console.WriteLine("================= Finished Training ================");
Console.WriteLine();
return(model);
}