learning

Type Members

1. class Answer extends AnyRef

   

   Evaluates the output of svm_rank_classify or other reranking classifier This currently computes P@1 This works for the QA system, but it should work for every generic svm_rank_classify like output User: mihais Date: 9/11/13

2. class BVFDataset[L, F] extends Dataset[L, F]

   

   Dataset containing only BVFDatums Important note: to encode feature values > 1, simply store the same feature multiple times (equal to feature value)!

   Dataset containing only BVFDatums Important note: to encode feature values > 1, simply store the same feature multiple times (equal to feature value)!

   L

   Type of labels

   F

   Type of features

3. class BVFDatum[L, F] extends Datum[L, F]

   

   Datum that contains only binary- (or Int) valued features

4. class BVFRankingDataset[F] extends RankingDataset[F]

   

5. class BaggingClassifier[L, F] extends Classifier[L, F]

   

   Classifier that implements bagging over another Classifier Created by dfried, mihais Date: 4/25/14

6. trait Classifier[L, F] extends AnyRef

   

   Trait for iid classification For reranking problems, see RankingClassifier User: mihais Date: 11/17/13

7. class CounterDataset[L, F] extends Dataset[L, F]

   

   Dataset that represents datums as explicit counters This is more efficient for the training of various algorithms such as random forests

8. abstract class Dataset[L, F] extends Serializable

   

   Parent class for classification datasets User: mihais Date: 4/23/13

9. class DatasetFold extends AnyRef

   

   Stores one fold, containing testing and training partitions Each tuple stores start and end offsets, starting from 0 User: mihais Date: 5/1/13

10. class Datasets extends AnyRef

    

    Operations on datasets User: mihais Date: 5/1/13

11. trait Datum[L, F] extends AnyRef

    

    Trait for ML datums.

    Trait for ML datums. L indicates the type of the label; F indicates the type of the feature User: mihais Date: 4/23/13

12. trait FeatureTraversable[F, V] extends AnyRef

    

    Analogous to iterable -- defines a method for geting the feature traverser and updater Created by dfried on 5/27/14.

13. trait FeatureUpdater[F, V] extends Traversable[(F, V)]

    

    Allows traversal of a dataset (or ranking dataset)'s features and values, and also destructive updates of the values.

    Allows traversal of a dataset (or ranking dataset)'s features and values, and also destructive updates of the values. Useful for finding the range of values and then rescaling them. Analogous to iterator with destructive updates Created by dfried on 5/27/14.

14. class InformationGain extends AnyRef

    

15. class KernelType extends AnyRef

    

16. class L1LinearSVMClassifier[L, F] extends LiblinearClassifier[L, F]

    

    Linear SVM with L1 regularization

17. class L1LogisticRegressionClassifier[L, F] extends LiblinearClassifier[L, F]

    

    LR with L1 regularization

18. class LibSVMClassifier[L, F] extends Classifier[L, F] with Serializable

    

    Modified from mihais's Liblinear wrapper by dfried on 5/2/14

19. class LiblinearClassifier[L, F] extends Classifier[L, F] with Serializable

    

    Wrapper for liblinear classifiers, which includes LR and linear SVM Note: this only supports classification; it does not support regression by design User: mihais Date: 11/16/13

20. class LinearSVMClassifier[L, F] extends LiblinearClassifier[L, F]

    

    Linear SVM with L2 regularization

21. class LogisticRegressionClassifier[L, F] extends LiblinearClassifier[L, F]

    

    Vanilla logistic regression with L2 regularization

22. class PerceptronClassifier[L, F] extends Classifier[L, F] with Serializable

    

    Multiclass perceptron classifier, in primal mode Includes averaging, hard margin, burn-in iterations User: mihais Date: 12/15/13

23. class PerceptronRankingClassifier[F] extends RankingClassifier[F] with Serializable

    

    Perceptron classifier for ranking, in primal mode Includes averaging, hard margin, burn-in iterations User: mihais Date: 12/10/13

24. class Qid extends AnyRef

    

25. class RFClassifier[L, F] extends Classifier[L, F] with Serializable

    

    An in-house implementation of random forests User: mihais Date: 11/23/15

26. class RFJob[L, F] extends AnyRef

    

27. class RFLeaf extends RFTree

    

28. class RFNonTerminal extends RFTree

    

29. trait RFTree extends AnyRef

    

30. class RVFDataset[L, F] extends BVFDataset[L, F] with FeatureTraversable[F, Double]

    

    Dataset containing only RVFDatums

    Dataset containing only RVFDatums

    L

    Type of labels

    F

    Type of features

31. class RVFDatum[L, F] extends Datum[L, F]

    

    Datum that contains real-valued features

32. class RVFKDatum[L, F] extends RVFDatum[L, F]

    

    Datum that contains real-valued features and kernelized representation

33. class RVFKRankingDataset[F] extends RVFRankingDataset[F]

    

34. class RVFRankingDataset[F] extends BVFRankingDataset[F] with FeatureTraversable[F, Double]

    

35. trait RankingClassifier[F] extends AnyRef

    

    Generic trait for ranking classifiers; for iid classification see Classifier User: mihais Date: 4/23/13

36. trait RankingDataset[F] extends AnyRef

    

    Parent class for all datasets used for ranking problems User: mihais Date: 4/23/13

37. class SVMRankingClassifier[F] extends RankingClassifier[F] with Serializable

    

    Wrapper for SVMrank: trains using svm_rank_learn but predicts using native Scala code Only the linear kernel is supported User: mihais Date: 4/23/13

38. class ScaleRange[F] extends Serializable

    

39. case class Utility(feature: Int, threshold: Double, value: Double, parentValue: Double, leftChildValue: Double, rightChildValue: Double, leftCounter: Counter[Int], rightCounter: Counter[Int]) extends Product with Serializable