ml

Type Members

1. case class BrownClusters(clusters: Iterable[(Symbol, Seq[Int])]) extends Product with Serializable

   

2. case class FeatureEncoding(featureNames: IndexedSeq[FeatureName]) extends Product with Serializable

   

   Maps feature names to integers.

   Maps feature names to integers. Useful for serializing TrainingData instances for consumption by command-line machine learning tools.

   featureNames

   an indexed sequence of feature names

3. case class FeatureName(symbols: Seq[Symbol]) extends Product with Serializable

   

   The name of a feature, represented as a list of Symbols.

   The name of a feature, represented as a list of Symbols.

   symbols

   the list of symbols comprising the feature name

4. case class FeatureVector(values: Seq[(FeatureName, Double)]) extends Product with Serializable

   

   A mapping from feature names to values.

   A mapping from feature names to values.

   Unspecified feature names are assumed to correspond to a value of zero.

   values

   the map from feature names to values

5. case class LinearModel(coefficients: Seq[(FeatureName, Double)]) extends Product with Serializable

   

   A weighted linear combination of features.

   A weighted linear combination of features.

   coefficients

   map from feature names to weight coefficients

6. case class TrainingData(labeledVectors: Iterable[(FeatureVector, Int)]) extends Product with Serializable

   

   Abstraction for a set of labeled feature vectors.

   Abstraction for a set of labeled feature vectors.

   Provides various serialization options for different machine learning tools.

   labeledVectors

   a sequence of feature vectors labeled with integer outcomes

7. case class Verbnet(groupName: String, artifactName: String, version: Int) extends Product with Serializable

   

   A class that uses JVerbnet, a 3rd party Wrapper library for Verbnet data (http://projects.csail.mit.edu/jverbnet/), to quickly look up various vernbet features for a verb.

8. case class WrapperClassifier(classifier: ProbabilisticClassifier, featureNameMap: Seq[(Int, FeatureName)]) extends Product with Serializable

   

   A WrapperClassifier wraps a ProbabilisticClassifier (which uses integer-based feature names) in an interface that allows you to use the more natural org.allenai.nlpstack.parse.poly.ml FeatureVector format for classification.

   A WrapperClassifier wraps a ProbabilisticClassifier (which uses integer-based feature names) in an interface that allows you to use the more natural org.allenai.nlpstack.parse.poly.ml FeatureVector format for classification.

   classifier

   the embedded classifier (which uses integer-based feature names)

   featureNameMap

   a map from the integer feature names to their string-based form

9. class WrapperClassifierTrainer extends AnyRef

   

   Trains a WrapperClassifier from training data.