private static void PrintClassificationMetrics(string name, MultiClassClassifierEvaluator.Result metrics)
{
Console.WriteLine($"*************************************************");
Console.WriteLine($"* Metrics for {name} ");
Console.WriteLine($"*------------------------------------------------");
Console.WriteLine($"* Accuracy Macro: {metrics.AccuracyMacro}");
Console.WriteLine($"* Accuracy Micro: {metrics.AccuracyMicro}");
Console.WriteLine($"* Log Loss: {metrics.LogLoss}");
Console.WriteLine($"* Log Loss Reduction: {metrics.LogLossReduction}");
Console.WriteLine($"* Per Class Log Loss: {metrics.PerClassLogLoss}");
Console.WriteLine($"*************************************************");
}
private void CompareMatrics(MultiClassClassifierEvaluator.Result metrics)
{
Assert.Equal(.98, metrics.AccuracyMacro);
Assert.Equal(.98, metrics.AccuracyMicro, 2);
Assert.InRange(metrics.LogLoss, .05, .06);
Assert.InRange(metrics.LogLossReduction, 94, 96);
Assert.Equal(3, metrics.PerClassLogLoss.Length);
Assert.Equal(0, metrics.PerClassLogLoss[0], 1);
Assert.Equal(.1, metrics.PerClassLogLoss[1], 1);
Assert.Equal(.1, metrics.PerClassLogLoss[2], 1);
}
public static void PrintMultiClassClassificationMetrics(string name, MultiClassClassifierEvaluator.Result metrics)
{
Console.WriteLine($"************************************************************");
Console.WriteLine($"* Metrics for {name} multi-class classification model ");
Console.WriteLine($"*-----------------------------------------------------------");
Console.WriteLine($" AccuracyMacro = {metrics.AccuracyMacro:0.####}, a value between 0 and 1, the closer to 1, the better");
Console.WriteLine($" AccuracyMicro = {metrics.AccuracyMicro:0.####}, a value between 0 and 1, the closer to 1, the better");
Console.WriteLine($" LogLoss = {metrics.LogLoss:0.####}, the closer to 0, the better");
Console.WriteLine($" LogLoss for class 1 = {metrics.PerClassLogLoss[0]:0.####}, the closer to 0, the better");
Console.WriteLine($" LogLoss for class 2 = {metrics.PerClassLogLoss[1]:0.####}, the closer to 0, the better");
Console.WriteLine($" LogLoss for class 3 = {metrics.PerClassLogLoss[2]:0.####}, the closer to 0, the better");
Console.WriteLine($"************************************************************");
}
public static void ToConsole(this MultiClassClassifierEvaluator.Result result)
{
Console.WriteLine($"Acuracy macro: {result.AccuracyMacro}");
Console.WriteLine($"Acuracy micro: {result.AccuracyMicro}");
Console.WriteLine($"Log loss: {result.LogLoss}");
Console.WriteLine($"Log loss reduction: {result.LogLossReduction}");
Console.WriteLine($"Per class log loss: ");
int count = 0;
foreach (var logLossClass in result.PerClassLogLoss)
{
Console.WriteLine($"\t [{count++}]: {logLossClass}");
}
Console.WriteLine($"Top K: {result.TopK}");
Console.WriteLine($"Top K accuracy: {result.TopKAccuracy}");
}
