public static void ToConsole(this RegressionEvaluator.Result result)
{
Console.WriteLine($"L1: {result.L1}");
Console.WriteLine($"L2: {result.L2}");
Console.WriteLine($"Loss function: {result.LossFn}");
Console.WriteLine($"Root mean square of the L2 loss: {result.Rms}");
Console.WriteLine($"R scuared: {result.RSquared}");
}
public RegressionEvaluator.Result Evaluate(MLContext mlContext, ITransformer model, string testDataPath, TextLoader textLoader)
{
IDataView dataView = textLoader.Read(testDataPath);
var predictions = model.Transform(dataView);
RegressionEvaluator.Result metrics = mlContext.Regression.Evaluate(predictions, "Label", "Score");
return(metrics);
}
private static RegressionEvaluator.Result RegressionDelta(
RegressionEvaluator.Result a, RegressionEvaluator.Result b)
{
return(new RegressionEvaluator.Result(
l1: a.L1 - b.L1,
l2: a.L2 - b.L2,
rms: a.Rms - b.Rms,
lossFunction: a.LossFn - b.LossFn,
rSquared: a.RSquared - b.RSquared));
}
private static void DisplayMetrics(RegressionEvaluator.Result metrics)
{
Console.WriteLine();
Console.WriteLine(new String('=', 35));
Console.WriteLine("Model quality metrics evaluation");
Console.WriteLine();
Console.WriteLine($"* R2 Score: {metrics.RSquared:0.##}");
Console.WriteLine($"* RMS loss: {metrics.Rms:#.##}");
Console.WriteLine(new String('=', 35));
}
public static void PrintRegressionMetrics(string name, RegressionEvaluator.Result metrics)
{
Console.WriteLine($"*************************************************");
Console.WriteLine($"* Metrics for {name} regression model ");
Console.WriteLine($"*------------------------------------------------");
Console.WriteLine($"* LossFn: {metrics.LossFn:0.##}");
Console.WriteLine($"* R2 Score: {metrics.RSquared:0.##}");
Console.WriteLine($"* Absolute loss: {metrics.L1:#.##}");
Console.WriteLine($"* Squared loss: {metrics.L2:#.##}");
Console.WriteLine($"* RMS loss: {metrics.Rms:#.##}");
Console.WriteLine($"*************************************************");
}
