public override double[] GetOutputs(float[][] rows)
{
return(Booster.PredictForMats(Booster.PredictType.Normal, rows, MaxNumTrees));
}
private protected override IVectorisedPredictorWithFeatureWeights <double> CreateNativePredictor()
{
return(new BinaryNativePredictor(Booster.Clone()));
}
public void Dispose()
{
Booster.Dispose();
}
public BinaryNativePredictor(Booster booster) : base(booster)
{
}
public NativePredictorBase(Booster booster)
{
Booster = booster;
MaxNumTrees = booster.BestIteration < 0 ? booster.CurrentIteration : booster.BestIteration;
}
public void GetOutput(ref VBuffer <float> features, ref TOutput prob)
{
var output = Booster.PredictForMat(Booster.PredictType.Normal, features.Values, MaxNumTrees);
prob = ConvertOutput(output);
}
public MulticlassNativePredictor(Booster booster) : base(booster)
{
}
public void GetOutput(ref VBuffer <float> features, ref TOutput prob, int startIteration, int numIterations)
{
var output = Booster.PredictForMat(Booster.PredictType.Normal, features.Values, startIteration, (numIterations == -1) ? MaxNumTrees : numIterations);
prob = ConvertOutput(output);
}
public override double[] GetOutputs(float[][] rows, int startIteration, int numIterations)
{
return(Booster.PredictForMats(Booster.PredictType.Normal, rows, startIteration, (numIterations == -1) ? MaxNumTrees : numIterations, MaxThreads));
}
public RegressionNativePredictor(Booster booster) : base(booster)
{
}
public void MergeWith(Booster other)
{
Check.NonNull(other, nameof(other));
PInvokeException.Check(PInvoke.BoosterMerge(Handle, other.Handle),
nameof(PInvoke.BoosterMerge));
}
