TVectorPredictor Train(RoleMappedData data)
{
Contracts.CheckValue(data, "data");
data.CheckFeatureFloatVector();
int count;
data.CheckMulticlassLabel(out count);
using (var ch = Host.Start("Training"))
{
// Train one-vs-all models.
_predictors = new TVectorPredictor[1];
for (int i = 0; i < _predictors.Length; i++)
{
ch.Info("Training learner {0}", i);
Contracts.CheckValue(_args.predictorType, "predictorType", "Must specify a base learner type");
TScalarTrainer trainer;
if (_trainer != null)
{
trainer = _trainer;
}
else
{
var temp = ScikitSubComponent <ITrainer, SignatureBinaryClassifierTrainer> .AsSubComponent(_args.predictorType);
var inst = temp.CreateInstance(Host);
trainer = inst as TScalarTrainer;
if (trainer == null)
{
var allTypes = TrainerHelper.GetParentTypes(inst.GetType()).ToArray();
var allTypesStr = string.Join("\n", allTypes.Select(c => c.ToString()));
throw ch.ExceptNotSupp($"Unable to cast {inst.GetType()} into {typeof(TScalarTrainer)}.\n-TYPES-\n{allTypesStr}");
}
}
_trainer = null;
_predictors[i] = TrainPredictor(ch, trainer, data, count);
}
}
return(CreatePredictor());
}
protected override TVectorPredictor Train(TrainContext context)
{
var data = context.TrainingSet;
Contracts.CheckValue(data, "data");
data.CheckFeatureFloatVector();
int count;
data.CheckMulticlassLabel(out count);
using (var ch = Host.Start("Training"))
{
// Train one-vs-all models.
_predictors = new TVectorPredictor[1];
for (int i = 0; i < _predictors.Length; i++)
{
ch.Info("Training learner {0}", i);
Contracts.CheckValue(_args.predictorType, "predictorType", "Must specify a base learner type");
TScalarTrainer trainer;
if (_trainer != null)
{
trainer = _trainer;
}
else
{
var trSett = ScikitSubComponent <ITrainer, SignatureTrainer> .AsSubComponent(_args.predictorType);
var tr = trSett.CreateInstance(Host);
trainer = tr as TScalarTrainer;
Contracts.AssertValue(trainer);
}
_trainer = null;
_predictors[i] = TrainPredictor(ch, trainer, data, count);
}
}
return(CreatePredictor());
}
TVectorPredictor Train(RoleMappedData data)
{
Contracts.CheckValue(data, "data");
data.CheckFeatureFloatVector();
int count;
data.CheckMultiClassLabel(out count);
using (var ch = Host.Start("Training"))
{
// Train one-vs-all models.
_predictors = new TVectorPredictor[1];
for (int i = 0; i < _predictors.Length; i++)
{
ch.Info("Training learner {0}", i);
Contracts.CheckValue(_args.predictorType, "predictorType", "Must specify a base learner type");
TScalarTrainer trainer;
if (_trainer != null)
{
trainer = _trainer;
}
else
{
var temp = ScikitSubComponent <ITrainer, SignatureBinaryClassifierTrainer> .AsSubComponent(_args.predictorType);
trainer = temp.CreateInstance(Host) as TScalarTrainer;
}
_trainer = null;
_predictors[i] = TrainPredictor(ch, trainer, data, count);
}
}
return(CreatePredictor());
}
