c

undersampling.core

ClusterOSS

class ClusterOSS extends Algorithm

ClusterOSS. Original paper: "ClusterOSS: a new undersampling method for imbalanced learning." by Victor H Barella, Eduardo P Costa and André C P L F Carvalho.

Linear Supertypes
Algorithm, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. ClusterOSS
  2. Algorithm
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new ClusterOSS(data: Data, seed: Long = System.currentTimeMillis(), minorityClass: Any = -1)

    data

    data to work with

    seed

    seed to use. If it is not provided, it will use the system time

    minorityClass

    indicates the minority class. If it's set to -1, it will set to the one with less instances

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate() @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  8. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  9. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  10. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  11. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  13. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  14. def sample(file: Option[String] = None, distance: Distance = Distances.EUCLIDEAN, k: Int = 3, numClusters: Int = 15, restarts: Int = 5, minDispersion: Double = 0.0001, maxIterations: Int = 100): Data

    Undersampling method based in ClusterOSS

    Undersampling method based in ClusterOSS

    file

    file to store the log. If its set to None, log process would not be done

    distance

    distance to use when calling the NNRule algorithm

    k

    number of neighbours to use when computing k-NN rule (normally 3 neighbours)

    numClusters

    number of clusters to be created by KMeans algorithm

    restarts

    number of times to relaunch KMeans algorithm

    minDispersion

    stop KMeans algorithm if dispersion is lower than this value

    maxIterations

    number of iterations to be done in KMeans algorithm

    returns

    Data structure with all the important information

  15. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  16. def toString(): String
    Definition Classes
    AnyRef → Any
  17. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  18. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  19. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @Deprecated @deprecated @throws( classOf[java.lang.Throwable] )
    Deprecated

    (Since version ) see corresponding Javadoc for more information.

Inherited from Algorithm

Inherited from AnyRef

Inherited from Any

Ungrouped