/// <summary>
/// Writes the precision-recall curve to the file with the specified name.
/// </summary>
/// <param name="fileName">The name of the file to write the precision-recall curve to.</param>
/// <param name="evaluator">The classifier evaluator.</param>
/// <param name="groundTruth">The ground truth.</param>
/// <param name="predictiveDistributions">The predictive distributions.</param>
/// <param name="positiveClassLabel">The label of the positive class.</param>
private void WritePrecisionRecallCurve(
string fileName,
ClassifierEvaluator <IList <LabeledFeatureValues>, LabeledFeatureValues, IList <LabelDistribution>, string> evaluator,
IList <LabeledFeatureValues> groundTruth,
IList <IDictionary <string, double> > predictiveDistributions,
string positiveClassLabel)
{
Debug.Assert(predictiveDistributions != null, "The predictive distributions must not be null.");
Debug.Assert(predictiveDistributions.Count > 0, "The predictive distributions must not be empty.");
Debug.Assert(positiveClassLabel != null, "The label of the positive class must not be null.");
var precisionRecallCurve = evaluator.PrecisionRecallCurve(positiveClassLabel, groundTruth, predictiveDistributions);
using (var writer = new StreamWriter(fileName))
{
writer.WriteLine("# Precision-recall curve");
writer.WriteLine("#");
writer.WriteLine("# Class '" + positiveClassLabel + "' (versus the rest)");
writer.WriteLine("#");
writer.WriteLine("# precision (P), Recall (R)");
foreach (var point in precisionRecallCurve)
{
writer.WriteLine(point);
}
}
}
/// <summary>
/// Writes the precision-recall curve to the file with the specified name.
/// </summary>
/// <param name="fileName">The name of the file to write the precision-recall curve to.</param>
/// <param name="evaluator">The classifier evaluator.</param>
/// <param name="x">The x vector of the ground truth.</param>
/// <param name="y">The y of the ground truth.</param>
/// <param name="yPredicDistrib">The predictive distributions.</param>
/// <param name="positiveClassLabel">The label of the positive class.</param>
/// <remarks>Adapted from MicrosoftResearch.Infer.Learners</remarks>
private void WritePrecisionRecallCurve(
string fileName,
ClassifierEvaluator <IList <Vector>, int, IList <string>, string> evaluator,
Vector[] x,
IList <string> y,
IEnumerable <IDictionary <string, double> > yPredicDistrib,
string positiveClassLabel)
{
Debug.Assert(yPredicDistrib != null, "The predictive distributions must not be null.");
Debug.Assert(yPredicDistrib.Count() > 0, "The predictive distributions must not be empty.");
Debug.Assert(positiveClassLabel != null, "The label of the positive class must not be null.");
var precisionRecallCurve = evaluator.PrecisionRecallCurve(positiveClassLabel, x, y, yPredicDistrib);
using (var writer = new StreamWriter(fileName))
{
writer.WriteLine("# Precision-recall curve");
writer.WriteLine("#");
writer.WriteLine("# Class '" + positiveClassLabel + "' (versus the rest)");
writer.WriteLine("#");
writer.WriteLine("# Recall (R), precision (P)");
foreach (var point in precisionRecallCurve)
{
writer.WriteLine("{0}, {1}", point.First, point.Second);
}
}
}