axle.ml.KMeansModule

KMeansClassifier

case class KMeansClassifier[T](data: Seq[T], N: Int, featureExtractor: (T) ⇒ Seq[Double], constructor: (Seq[Double]) ⇒ T, space: MetricSpace[matrix.JblasMatrixModule.Matrix[Double], Double], K: Int, iterations: Int) extends Product with Serializable

KMeansClassifier[T]

T

type of the objects being classified

N

number of features

featureExtractor

creates a list of features (Doubles) of length N given a T

constructor

creates a T from list of arguments of length N

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Instance Constructors

  1. new KMeansClassifier(data: Seq[T], N: Int, featureExtractor: (T) ⇒ Seq[Double], constructor: (Seq[Double]) ⇒ T, space: MetricSpace[matrix.JblasMatrixModule.Matrix[Double], Double], K: Int, iterations: Int)

    N

    number of features

    featureExtractor

    creates a list of features (Doubles) of length N given a T

    constructor

    creates a T from list of arguments of length N

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  6. val K: Int

  7. val N: Int

    number of features

  8. val X: matrix.JblasMatrixModule.Matrix[Double]

  9. val a: matrix.JblasMatrixModule.Matrix[Int]

  10. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  11. val assignmentLog: Seq[matrix.JblasMatrixModule.Matrix[Int]]

  12. def assignmentsAndDistances(space: MetricSpace[matrix.JblasMatrixModule.Matrix[Double], Double], X: matrix.JblasMatrixModule.Matrix[Double], μ: matrix.JblasMatrixModule.Matrix[Double]): (matrix.JblasMatrixModule.Matrix[Int], matrix.JblasMatrixModule.Matrix[Double])

    assignmentsAndDistances

    assignmentsAndDistances

    X
    μ

    Returns: N x 1 matrix: indexes of centroids closest to xi N x 1 matrix: distances to those centroids

  13. def centroidIndexAndDistanceClosestTo(space: MetricSpace[matrix.JblasMatrixModule.Matrix[Double], Double], μ: matrix.JblasMatrixModule.Matrix[Double], x: matrix.JblasMatrixModule.Matrix[Double]): (Int, Double)

    centroidIndexAndDistanceClosestTo

    centroidIndexAndDistanceClosestTo

    μ
    x

  14. def centroids(X: matrix.JblasMatrixModule.Matrix[Double], K: Int, assignments: matrix.JblasMatrixModule.Matrix[Int]): (matrix.JblasMatrixModule.Matrix[Double], Seq[Int])

    centroids

    centroids

    X

    M x N scaled feature matrix

    K

    number of centroids

  15. def classify(observation: T): Int

  16. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()

  17. def clusterLA(X: matrix.JblasMatrixModule.Matrix[Double], space: MetricSpace[matrix.JblasMatrixModule.Matrix[Double], Double], K: Int, iterations: Int): Seq[(matrix.JblasMatrixModule.Matrix[Double], matrix.JblasMatrixModule.Matrix[Int], matrix.JblasMatrixModule.Matrix[Double])]

    clusterLA

    clusterLA

    X

    (normalized feature matrix)

    K
    iterations

  18. def confusionMatrix[L](data: Seq[T], labelExtractor: (T) ⇒ L): ConfusionMatrix[T, L]

  19. val constructor: (Seq[Double]) ⇒ T

    creates a T from list of arguments of length N

  20. val d: matrix.JblasMatrixModule.Matrix[Double]

  21. val data: Seq[T]

  22. val distanceLog: Seq[matrix.JblasMatrixModule.Matrix[Double]]

  23. def distanceLogSeries(): List[(String, TreeMap[Int, Double])]

  24. def distanceTreeMap(centroidId: Int): TreeMap[Int, Double]

  25. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  26. def exemplar(i: Int): T

  27. val exemplars: List[T]

  28. val featureExtractor: (T) ⇒ Seq[Double]

    creates a list of features (Doubles) of length N given a T

  29. val features: matrix.JblasMatrixModule.Matrix[Double]

  30. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()

  31. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  32. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  33. val iterations: Int

  34. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  35. val normalizer: FeatureNormalizerModule.PCAFeatureNormalizer

  36. final def notify(): Unit

    Definition Classes
    AnyRef

  37. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  38. val space: MetricSpace[matrix.JblasMatrixModule.Matrix[Double], Double]

  39. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  40. final def wait(): Unit

    Definition Classes
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    @throws()

  41. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
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    @throws()

  42. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
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    @throws()

  43. val μ: matrix.JblasMatrixModule.Matrix[Double]

  44. val μads: Seq[(matrix.JblasMatrixModule.Matrix[Double], matrix.JblasMatrixModule.Matrix[Int], matrix.JblasMatrixModule.Matrix[Double])]

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

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