public override IDictionary <string, double> PredictInstance( string inputModelFileName, DistributionName distributionName, InferenceAlgorithm inferenceEngineAlgorithm, int instance, double noise) { TraceListeners.Log(TraceEventType.Warning, 0, "Advanced setting will not be used: " + "distributionName, inferenceEngineAlgorithm & noise.", false, true); // Validate _validate.PredictInstance( inputModelFileName: inputModelFileName, instance: instance, numObservations: _numObservations); IBayesPointMachineClassifier < IList <Vector>, int, IList <string>, string, IDictionary <string, double>, BayesPointMachineClassifierTrainingSettings, BinaryBayesPointMachineClassifierPredictionSettings <string> > classifier = null; // Load model if (string.IsNullOrEmpty(inputModelFileName)) { classifier = BayesPointMachineClassifier.LoadBinaryClassifier < IList <Vector>, int, IList <string>, string, IDictionary <string, double> > (inputModelFileName); } else { classifier = _classifier; } IDictionary <string, double> yPredicted = classifier.PredictDistribution(instance, _x); // string yPredicLabel = classifier.Predict(instance, _x); return(yPredicted); }
public override void Predict( string inputModelFileName, DistributionName distributionName, InferenceAlgorithm inferenceEngineAlgorithm, double noise) { TraceListeners.Log(TraceEventType.Warning, 0, "Advanced setting will not be used: " + "distributionName, inferenceEngineAlgorithm & noise.", false, true); // Validate _validate.Predict(inputModelFileName); // Define the classifier IBayesPointMachineClassifier < IList <Vector>, int, IList <string>, string, IDictionary <string, double>, BayesPointMachineClassifierTrainingSettings, BinaryBayesPointMachineClassifierPredictionSettings <string> > classifier = null; // Load model if (string.IsNullOrEmpty(inputModelFileName)) { classifier = BayesPointMachineClassifier.LoadBinaryClassifier < IList <Vector>, int, IList <string>, string, IDictionary <string, double> > (inputModelFileName); } else { classifier = _classifier; } _validate.ValidatePredict(_x, _x); _yPredicDistrib = classifier.PredictDistribution(_x); _yPredicLabel = classifier.Predict(_x); }