Package

org.clulab

learning

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package learning

Visibility
  1. Public
  2. All

Type Members

  1. class Answer extends AnyRef

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    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]

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    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]

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

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

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  5. class BVFRegDataset[F] extends RegDataset[F]

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

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

    F

    Type of features

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

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

  7. trait Classifier[L, F] extends AnyRef

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

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

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

  9. class CounterRegDataset[F] extends RegDataset[F]

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

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

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    Parent class for classification datasets User: mihais Date: 4/23/13 Last Modified: Fix compiler issue: import scala.io.Source.

  11. class DatasetFold extends AnyRef

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

  12. class Datasets extends AnyRef

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    Operations on datasets User: mihais Date: 5/1/13 Last Modified: Update for Scala 2.12: fork join changes.

  13. trait Datum[L, F] extends AnyRef

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    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

  14. trait FeatureTraversable[F, V] extends AnyRef

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

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

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    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.

  16. class InformationGain extends AnyRef

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  17. class KernelType extends AnyRef

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

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    Linear SVM with L1 regularization

  19. class L1LinearSVMRegression[F] extends LiblinearRegression[F]

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    L2-regularized L1-loss support vector regression (dual)

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

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    LR with L1 regularization

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

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    Modified from mihais's Liblinear wrapper by dfried on 5/2/14 Further modified by enrique on 5/15/18

  22. class LibSvmEpsilonRegression[F] extends LibSvmRegression[F]

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  23. class LibSvmNuRegression[F] extends LibSvmRegression[F]

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  24. class LibSvmRegression[F] extends Regression[F] with Serializable

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    Wrapper for libsvm regression User: mihais, dfried, danebell Date: 11/20/2017

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

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    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

  26. class LiblinearRegression[F] extends Regression[F] with Serializable

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    Wrapper for liblinear regression, including LR and linear SVM User: mihais, danebell Date: 11/15/17

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

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    Linear SVM with L2 regularization

  28. class LinearSVMRegression[F] extends LiblinearRegression[F]

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    L2-regularized L2-loss support vector regression (primal)

  29. class LinearSVMRegressionDual[F] extends LiblinearRegression[F]

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    L2-regularized L2-loss support vector regression (dual)

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

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    Vanilla logistic regression with L2 regularization

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

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

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

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

  33. class Qid extends AnyRef

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

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    An in-house implementation of random forests User: mihais Date: 11/23/15 Last Modified: Update for Scala 2.12: fork join changes.

  35. class RFJob[L, F] extends AnyRef

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  36. class RFLeaf extends RFTree

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  37. class RFNonTerminal extends RFTree

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  38. trait RFTree extends AnyRef

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

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    Dataset containing only RVFDatums

    Dataset containing only RVFDatums

    L

    Type of labels

    F

    Type of features

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

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    Datum that contains real-valued features

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

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    Datum that contains real-valued features and kernelized representation

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

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

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  44. class RVFRegDataset[F] extends BVFRegDataset[F] with FeatureTraversable[F, Double]

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    RegDataset containing only RVFDatums

    RegDataset containing only RVFDatums

    F

    Type of features

  45. trait RankingClassifier[F] extends AnyRef

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

  46. trait RankingDataset[F] extends AnyRef

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    Parent class for all datasets used for ranking problems User: mihais Date: 4/23/13 Last Modified: Fix compiler issue: import scala.io.Source.

  47. abstract class RegDataset[F] extends Serializable

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    Parent class for regression datasets.

    Parent class for regression datasets. For classification, see Dataset. User: mihais, danebell Date: 11/15/17

  48. trait Regression[F] extends AnyRef

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    Trait for regression Adapted from Classifier trait User: mihais, danebell Date: 11/15/17

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

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    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 Last Modified: Fix compiler issue: import scala.io.Source.

  50. class ScaleRange[F] extends Serializable

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  51. class SvmType extends AnyRef

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  52. 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

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Value Members

  1. object BaggingClassifier

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  2. object Datasets

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  3. object EpsilonSVR extends SvmType with Product with Serializable

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  4. object LearningExample

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    Simple example of how to use RVF data and classifiers User: mihais Date: 11/18/15

  5. object LibSVMClassifier extends Serializable

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  6. object LibSvmRegression extends Serializable

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  7. object LiblinearClassifier extends Serializable

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  8. object LiblinearRegression extends Serializable

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  9. object LinearKernel extends KernelType with Product with Serializable

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  10. object NuSVR extends SvmType with Product with Serializable

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  11. object PerceptronClassifier extends Serializable

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  12. object PerceptronRankingClassifier extends Serializable

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  13. object PolynomialKernel extends KernelType with Product with Serializable

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  14. object RBFKernel extends KernelType with Product with Serializable

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  15. object RFClassifier extends Serializable

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  16. object RVFDataset extends Serializable

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  17. object RVFRankingDataset

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  18. object RVFRegDataset extends Serializable

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  19. object RankerEvaluator

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  20. object RankingClassifier

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  21. object SVMRankingClassifier extends Serializable

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  22. object ScaleRange extends Serializable

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  23. object SigmoidKernel extends KernelType with Product with Serializable

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Ungrouped