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($"* RMS loss: {metrics.Rms:#.##}"); Console.WriteLine($"*************************************************"); }