DataBalancer

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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 apply(sampleFraction: Double = ..., maxTrainingSample: Int = ..., seed: Long = SplitterParamsDefault.seedDefault, reserveTestFraction: Double = ...): DataBalancer

   

   Creates an instance that will balance the dataset by doing upsample and downsample.

   Creates an instance that will balance the dataset by doing upsample and downsample. Splitting is also possible.

   sampleFraction

   desired minimum fraction of the minority class after balancing

   maxTrainingSample

   maximum size of training set

   seed

   seed for spliting and balancing

   reserveTestFraction

   fraction of the data used for test

   returns

   data balancer

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9. def finalize(): Unit

   

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

    

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