// load
public ModelMLNet(string path)
{
#if ML_LEGACY
TrainedModel = PredictionModel.ReadAsync <ModelDataSet, ModelDataSetPrediction>(path).Result;
#else
Context = new MLContext();
// load
using (var stream = new FileStream(path, FileMode.Open, FileAccess.Read, FileShare.Read))
{
TrainedModel = Context.Model.Load(stream);
}
// create the prediction function
PredictFunc = TrainedModel.MakePredictionFunction <ModelDataSet, ModelDataSetPrediction>(Context);
#endif
}
public ITransformer Train(IDataView trainingData)
{
TrainedModel = _trainingPipeline.Fit(trainingData);
PredictionFunction = TrainedModel.MakePredictionFunction <DemandObservation, DemandPrediction>(_mlcontext);
return(TrainedModel);
}
