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object ClassifierReal

The ClassifierReal object provides helper methods.

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  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. def analyzer(model: ClassifierReal): Unit

    Analyze a dataset using the given model using ordinary training with the 'train' method.

    Analyze a dataset using the given model using ordinary training with the 'train' method.

    model

    the model to be used

  5. final def asInstanceOf[T0]: T0
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  6. def clone(): AnyRef
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  7. final def eq(arg0: AnyRef): Boolean
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  9. final def getClass(): Class[_]
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  10. def hashCode(): Int
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  11. final def isInstanceOf[T0]: Boolean
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  12. def makeIsCont(size: Int, cont: Int*): Array[Boolean]

    Make the 'isCont' flag that indicates which columns are continuous.

    Make the 'isCont' flag that indicates which columns are continuous. Ex: makeIsCont (12, 7, 11) // 12 columns with 7 and 11 being continuous

    size

    the number of variables/features

    cont

    the column indices of the continuous variables/features

  13. final def ne(arg0: AnyRef): Boolean
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  14. final def notify(): Unit
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  15. final def notifyAll(): Unit
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  16. def pullResponse(xy: MatriD, col: Int = -1): (MatriD, VectoI)

    Pull out the designed response column from the combined matrix.

    Pull out the designed response column from the combined matrix. When 'col' is negative or the last column, slice out the last column.

    xy

    the combined data and response/classification matrix

    col

    the designated response column to be pulled out

  17. final def synchronized[T0](arg0: ⇒ T0): T0
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  18. def toString(): String
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  19. final def wait(arg0: Long, arg1: Int): Unit
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  20. final def wait(arg0: Long): Unit
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  21. final def wait(): Unit
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  1. def finalize(): Unit
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