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)); }