breeze.classify

LiblinearClassifier

class LiblinearClassifier extends AnyRef

A simple wrapper to Liblinear.

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Instance Constructors

  1. new LiblinearClassifier(model: Model)

Value Members

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

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

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  3. final def ##(): Int

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

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

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  6. def apply(nodes: Seq[FeatureNode]): Int

  7. final def asInstanceOf[T0]: T0

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  8. def clone(): AnyRef

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

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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

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  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. lazy val numClasses: Int

  19. def predict(nodes: Seq[FeatureNode]): Int

  20. def predictDense(inputValues: Seq[Double]): Int

  21. def predictValues(nodes: Seq[FeatureNode]): Seq[Double]

  22. def predictValuesBinary(nodes: Seq[FeatureNode]): Double

    This is an alternative to predictValues that assumes binary classification and assumes that the model won't be asked to use an out-of-bounds feature, both of which cut down on overhead.

    This is an alternative to predictValues that assumes binary classification and assumes that the model won't be asked to use an out-of-bounds feature, both of which cut down on overhead. It will give out-of-bounds exceptions if not used appropriately, and will not work at all for polytomous models.

  23. def predictValuesBinarySlow(nodes: Seq[FeatureNode]): Double

    This is how we'd prefer to write predictValuesBinary, but unfortunately, the while loop is faster than the fold (by about a factor of two, it seems).

    This is how we'd prefer to write predictValuesBinary, but unfortunately, the while loop is faster than the fold (by about a factor of two, it seems). :(

  24. def predictValuesDense(inputValues: Seq[Double]): Seq[Double]

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

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  26. def toString(): String

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  27. final def wait(): Unit

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

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

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  30. lazy val weights: Array[Double]

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