internal static OvaPredictor Create(IHost host, bool useProb, TScalarPredictor[] predictors)
{
ImplBase impl;
using (var ch = host.Start("Creating OVA predictor"))
{
IValueMapperDist ivmd = null;
if (useProb &&
((ivmd = predictors[0] as IValueMapperDist) == null ||
ivmd.OutputType != NumberType.Float ||
ivmd.DistType != NumberType.Float))
{
ch.Warning($"{nameof(Ova.Arguments.UseProbabilities)} specified with {nameof(Ova.Arguments.PredictorType)} that can't produce probabilities.");
ivmd = null;
}
if (ivmd != null)
{
var dists = new IValueMapperDist[predictors.Length];
for (int i = 0; i < predictors.Length; ++i)
{
dists[i] = (IValueMapperDist)predictors[i];
}
impl = new ImplDist(dists);
}
else
{
impl = new ImplRaw(predictors);
}
}
return(new OvaPredictor(host, impl));
}
internal static OptimizedOVAPredictor Create(IHost host, bool useProb, TScalarPredictor[] predictors)
{
ImplBase impl;
using (var ch = host.Start("Creating OVA predictor"))
{
IValueMapperDist ivmd = null;
if (useProb &&
((ivmd = predictors[0] as IValueMapperDist) == null ||
ivmd.OutputType != NumberDataViewType.Single ||
ivmd.DistType != NumberDataViewType.Single))
{
ch.Warning("useProbabilities specified with basePredictor that can't produce probabilities.");
ivmd = null;
}
if (ivmd != null)
{
var dists = new IValueMapperDist[predictors.Length];
for (int i = 0; i < predictors.Length; ++i)
{
dists[i] = (IValueMapperDist)predictors[i];
}
impl = new ImplDist(dists);
}
else
{
impl = new ImplRaw(predictors);
}
}
return(new OptimizedOVAPredictor(host, impl));
}
internal static MultiToRankerPredictor Create <TLabel>(IHost host, VBuffer <TLabel> classes,
TScalarPredictor[] predictors, IPredictor reclassPredictor, bool singleColumn, bool labelKey)
{
IImplBase impl;
using (var ch = host.Start("Creating MultiToRanker predictor"))
impl = new ImplRaw <TLabel>(classes, predictors, reclassPredictor, singleColumn, labelKey);
return(new MultiToRankerPredictor(host, impl));
}
internal static OneVersusAllModelParameters Create(IHost host, OutputFormula outputFormula, TScalarPredictor[] predictors)
{
ImplBase impl;
using (var ch = host.Start("Creating OVA predictor"))
{
if (outputFormula == OutputFormula.Softmax)
{
impl = new ImplSoftmax(predictors);
return(new OneVersusAllModelParameters(host, impl));
}
// Caller of this function asks for probability output. We check if input predictor can produce probability.
// If that predictor can't produce probability, ivmd will be null.
IValueMapperDist ivmd = null;
if (outputFormula == OutputFormula.ProbabilityNormalization &&
((ivmd = predictors[0] as IValueMapperDist) == null ||
ivmd.OutputType != NumberDataViewType.Single ||
ivmd.DistType != NumberDataViewType.Single))
{
ch.Warning($"{nameof(OneVersusAllTrainer.Options.UseProbabilities)} specified with {nameof(OneVersusAllTrainer.Options.PredictorType)} that can't produce probabilities.");
ivmd = null;
}
// If ivmd is null, either the user didn't ask for probability or the provided predictors can't produce probability.
if (ivmd != null)
{
var dists = new IValueMapperDist[predictors.Length];
for (int i = 0; i < predictors.Length; ++i)
{
dists[i] = (IValueMapperDist)predictors[i];
}
impl = new ImplDist(dists);
}
else
{
impl = new ImplRaw(predictors);
}
}
return(new OneVersusAllModelParameters(host, impl));
}
