multilabel

Type Members

1. case class MultilabelModel[U, K, -A, +B <: U](modelId: ModelIdentity, featureNames: IndexedSeq[String], featureFunctions: IndexedSeq[GenAggFunc[A, Sparse]], labelsInTrainingSet: IndexedSeq[K], labelsOfInterest: Option[GenAggFunc[A, IndexedSeq[K]]], predictorProducer: () ⇒ (SparseFeatures, Labels[K], LabelIndices, SparseLabelDepFeatures) ⇒ Try[Map[K, Double]], numMissingThreshold: Option[Int], auditor: Auditor[U, Map[K, Double], B])(implicit ev: SerializabilityEvidence[K]) extends SubmodelBase[U, Map[K, Double], A, B] with RegressionFeatures[A] with Product with Serializable

   A multi-label predictor.

2. trait MultilabelModelParserPlugin extends AnyRef

   A plugin that will ultimately produce the SparseMultiLabelPredictor.

3. trait MultilabelPluginProviderCompanion extends AnyRef

   Created by ryan.

4. trait PluginInfo[K] extends AnyRef

   Created by ryan.

5. type SparseMultiLabelPredictor[K] = (SparseFeatures, Labels[K], LabelIndices, SparseLabelDepFeatures) ⇒ Try[Map[K, Double]]

   A sparse multi-label predictor takes:

   A sparse multi-label predictor takes:

   • features
   • labels for which a prediction should be produced
   • indices of those labels into sequence of all of the labels the model knows about.
   • label dependent-features

   and returns a Map from the labels passed in, to the prediction associated with the label.

6. type SparsePredictorProducer[K] = () ⇒ (SparseFeatures, Labels[K], LabelIndices, SparseLabelDepFeatures) ⇒ Try[Map[K, Double]]

   A lazy version of a sparse multi-label predictor.

   A lazy version of a sparse multi-label predictor. It is a curried zero-arg function that produces a sparse multi-label predictor.

   This definition is "lazy" because we can't guarantee that the underlying predictor is Serializable so we pass around a function that can be cached in a transient lazy val. This function should however be Serializable and testing should be done to ensure that each predictor producer is Serializable.