/// <summary>
/// Extracts the prediction, orders the action depdendent feature objects accordingly and appends the
/// action dependent feature objcts that did produce empty examples at the end.
/// </summary>
/// <typeparam name="TActionDependentFeature">The action dependent feature type.</typeparam>
/// <param name="vw">The Vowpal Wabbit instance.></param>
/// <param name="examples">The list of examples.</param>
/// <param name="validActionDependentFeatures">The list of non-empty action dependent feature objects.</param>
/// <param name="emptyActionDependentFeatures">The list of empty action dependent feature objects.</param>
/// <returns>Returns the ranked list of action dependent features.</returns>
public static ActionDependentFeature <TActionDependentFeature>[] GetPrediction <TActionDependentFeature>(
VowpalWabbit vw,
IReadOnlyList <VowpalWabbitExample> examples,
IReadOnlyList <ActionDependentFeature <TActionDependentFeature> > validActionDependentFeatures,
IReadOnlyList <ActionDependentFeature <TActionDependentFeature> > emptyActionDependentFeatures)
{
// Since the prediction result is stored in the first example
// and we'll have to get an actual VowpalWabbitExampt
var firstExample = examples.FirstOrDefault();
if (firstExample == null)
{
return(null);
}
var values = firstExample.GetPrediction(vw, VowpalWabbitPredictionType.Multilabel);
if (values.Length != validActionDependentFeatures.Count)
{
throw new InvalidOperationException("Number of predictions returned unequal number of examples fed");
}
var result = new ActionDependentFeature <TActionDependentFeature> [validActionDependentFeatures.Count + emptyActionDependentFeatures.Count];
int i = 0;
foreach (var index in values)
{
result[i++] = validActionDependentFeatures[index];
}
// append invalid ones at the end
foreach (var f in emptyActionDependentFeatures)
{
result[i++] = f;
}
return(result);
}
/// <summary>
/// Extracts the prediction, orders the action depdendent feature objects accordingly and appends the
/// action dependent feature objcts that did produce empty examples at the end.
/// </summary>
/// <typeparam name="TActionDependentFeature">The action dependent feature type.</typeparam>
/// <param name="vw">The Vowpal Wabbit instance.></param>
/// <param name="examples">The list of examples.</param>
/// <param name="validActionDependentFeatures">The list of non-empty action dependent feature objects.</param>
/// <param name="emptyActionDependentFeatures">The list of empty action dependent feature objects.</param>
/// <returns>Returns the ranked list of action dependent features.</returns>
public static ActionDependentFeature <TActionDependentFeature>[] GetPrediction <TActionDependentFeature>(
VowpalWabbit vw,
IReadOnlyList <VowpalWabbitExample> examples,
IReadOnlyList <ActionDependentFeature <TActionDependentFeature> > validActionDependentFeatures,
IReadOnlyList <ActionDependentFeature <TActionDependentFeature> > emptyActionDependentFeatures)
{
// Since the prediction result is stored in the first example
// and we'll have to get an actual VowpalWabbitExampt
var firstExample = examples.FirstOrDefault();
if (firstExample == null)
{
return(null);
}
ActionDependentFeature <TActionDependentFeature>[] result;
int i = 0;
var values = firstExample.GetPrediction(vw, VowpalWabbitPredictionType.Dynamic);
var actionScores = values as ActionScore[];
if (actionScores != null)
{
if (actionScores.Length != validActionDependentFeatures.Count)
{
throw new InvalidOperationException("Number of predictions returned unequal number of examples fed");
}
result = new ActionDependentFeature <TActionDependentFeature> [validActionDependentFeatures.Count + emptyActionDependentFeatures.Count];
foreach (var index in actionScores)
{
result[i] = validActionDependentFeatures[(int)index.Action];
result[i].Probability = index.Score;
i++;
}
}
else
{
var multilabel = values as int[];
if (multilabel != null)
{
if (multilabel.Length != validActionDependentFeatures.Count)
{
throw new InvalidOperationException("Number of predictions returned unequal number of examples fed");
}
result = new ActionDependentFeature <TActionDependentFeature> [validActionDependentFeatures.Count + emptyActionDependentFeatures.Count];
foreach (var index in multilabel)
{
result[i++] = validActionDependentFeatures[index];
}
result[0].Probability = 1f;
}
else
{
throw new NotSupportedException("Unsupported return type: " + values.GetType());
}
}
// append invalid ones at the end
foreach (var f in emptyActionDependentFeatures)
{
result[i++] = f;
}
return(result);
}
