Plotting

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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. final def asInstanceOf[T0]: T0

   

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5. def clone(): AnyRef

   

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

   

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7. def equals(arg0: Any): Boolean

   

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8. def finalize(): Unit

   

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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. final def ne(arg0: AnyRef): Boolean

    

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13. final def notify(): Unit

    

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14. final def notifyAll(): Unit

    

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15. def plotClf(data: List[List[Double]], labels: List[Int], clf: Classifier, name: String = "plots/clf.pdf"): Unit

    

    Plot labeled data and classifier decision

    Plot labeled data and classifier decision

    data

    List of features

    labels

    List of labels

    clf

    Trained classifier

    name

    Path to save the plot

16. def plotClfData(data: List[List[Double]], labels: List[Int], name: String = "plots/data.pdf"): Unit

    

    Plot labeled data

    Plot labeled data

    data

    List of features

    labels

    List of labels

    name

    Path to save the plot

17. def plotClfGrid(data: List[List[Double]], clf: Classifier, name: String = "plots/grid.pdf"): Unit

    

    Plot classifier decision areas on an envelope plane of the data

    Plot classifier decision areas on an envelope plane of the data

    data

    List of features

    clf

    Trained classifier

    name

    Path to save the plot

18. def plotClu(data: List[List[Double]], predictions: List[Int], clu: Clustering, drawCentroids: Boolean = false, name: String = "plots/clu.pdf"): Unit

    

    Plot data and cluster association.

    Plot data and cluster association. If dimensionality of data > 2, use first principal components as axes.

    data

    List of features

    predictions

    List of predicted classes

    clu

    Trained classifier

    name

    Path to save the plot

19. def plotCluGrid(data: List[List[Double]], clu: Clustering, name: String = "plots/grid.pdf"): Unit

    

    Plot clustering decision areas on an envelope plane of the data

    Plot clustering decision areas on an envelope plane of the data

    data

    List of features

    clu

    Trained clusterer

    name

    Path to save the plot

20. def plotCurves(curves: List[List[(Double, Double)]], names: List[String] = Nil, name: String = "plots/curves.pdf", xlabel: String = "Training epoch", ylabel: String = ""): Unit

    

    Plot a set of curves

    Plot a set of curves

    curves

    List of curves, with a curve being a list of points (x, y)

    names

    List of the curves' names

    name

    Path to save the plot

21. def plotReg(data: List[List[Double]], labels: List[Double], reg: Regressor, name: String = "plots/reg.pdf"): Unit

    

    Plot data for regression

    Plot data for regression

    data

    List of features, e.g. in 2D: x-coordinates

    labels

    List of labels, e.g. in 2D: y-coordinates

    reg

    Trained regressor

    name

    Path to save the plot

22. def plotRegData(data: List[List[Double]], labels: List[Double], name: String = "plots/data.pdf"): Unit

    

    Plot data for regression

    Plot data for regression

    data

    List of features, e.g. in 2D: x-coordinates

    labels

    List of labels, e.g. in 2D: y-coordinates

    name

    Path to save the plot

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

    

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24. def toString(): String

    

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25. final def wait(): Unit

    

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

    

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

    

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