scalation.analytics

ClassifierReal

abstract class ClassifierReal extends Classifier with Error

The ClassifierReal abstract class provides a common foundation for several classifiers that operate on real-valued data.

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Error, Classifier, AnyRef, Any
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Instance Constructors

  1. new ClassifierReal(x: MatrixD, y: VectorI, fn: Array[String], k: Int, cn: Array[String])

    x

    the real-valued training data vectors stored as rows of a matrix

    y

    the training classification vector, where y_i = class for row i of the matrix x

    fn

    the names for all features/variables

    k

    the number of classes

    cn

    the names for all classes

Abstract Value Members

  1. abstract def classify(z: VectorD): (Int, String)

    Given a new continuous data vector z, determine which class it belongs to.

    Given a new continuous data vector z, determine which class it belongs to.

    z

    the vector to classify

    Definition Classes
    Classifier
  2. abstract def train(): Unit

    Given a set of data vectors and their classifications, build a classifier.

    Given a set of data vectors and their classifications, build a classifier.

    Definition Classes
    Classifier

Concrete 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 classify(z: VectorI): (Int, String)

    Given a new discrete (integer-valued) data vector 'z', determine which class it belongs to, by first converting it to a vector of doubles.

    Given a new discrete (integer-valued) data vector 'z', determine which class it belongs to, by first converting it to a vector of doubles.

    z

    the vector to classify

    Definition Classes
    ClassifierRealClassifier
  6. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  7. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  8. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  9. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  10. def flaw(method: String, message: String): Unit

    Show the flaw by printing the error message.

    Show the flaw by printing the error message.

    method

    the method where the error occurred

    message

    the error message

    Definition Classes
    Error
  11. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  12. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  13. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  14. val m: Int

    the number of data vectors in training-set (# rows)

    the number of data vectors in training-set (# rows)

    Attributes
    protected
  15. val md: Double

    the training-set size as a Double

    the training-set size as a Double

    Attributes
    protected
  16. val n: Int

    the number of features/variables (# columns)

    the number of features/variables (# columns)

    Attributes
    protected
  17. val nd: Double

    the feature-set size as a Double

    the feature-set size as a Double

    Attributes
    protected
  18. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  19. final def notify(): Unit

    Definition Classes
    AnyRef
  20. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  21. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  22. def test(xx: MatrixD, yy: VectorI): Double

    Test the quality of the training with a test-set and return the fraction of correct classifications.

    Test the quality of the training with a test-set and return the fraction of correct classifications.

    xx

    the real-valued test vectors stored as rows of a matrix

    yy

    the test classification vector, where yy_i = class for row i of xx

  23. def toString(): String

    Definition Classes
    AnyRef → Any
  24. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  25. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  26. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Error

Inherited from Classifier

Inherited from AnyRef

Inherited from Any

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