sampleclean.activeml

ForestUncertaintyFilter

class ForestUncertaintyFilter[C <: PointLabelingContext] extends ActivePointSelector[RandomForestModel, C]

Uses uncertainty sampling to select points closest to the SVM Margin.

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ActivePointSelector[RandomForestModel, C], Serializable, Serializable, AnyRef, Any
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  1. new ForestUncertaintyFilter()

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  17. def selectPoints(input: RDD[(String, Vector, C)], nPoints: Int, model: RandomForestModel): (RDD[(String, Vector, C)], RDD[(String, Vector, C)])

    Splits points into two sets: the n that the random forest is least certain about, and all others.

    Splits points into two sets: the n that the random forest is least certain about, and all others. Uncertainty is simply calculated using variance among the trees in the forest

    input

    an RDD of unlabeled points in the form (id, feature vector, labeling context).

    nPoints

    The number of points to select.

    model

    A RandomForest model with trained weights.

    returns

    Two RDDs in the same format as input, one consisting of points close to the margin, the other consisting of the remaining points.

    Definition Classes
    ForestUncertaintyFilterActivePointSelector
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Inherited from ActivePointSelector[RandomForestModel, C]

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