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);
}