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M

m_allowNegativeValues - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
indicate if negative values are to be sampled. if false, sampled values are 0 as minimum
m_allowPoissonApproximation - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
indicates if sampling from a poisson distribution can be using an approximate way which reduces the sampling time and gets similar sampled values
m_balanceType - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
distribution to learn in order to re-sample new instances
m_labelsRange - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
range of selected label indexes to balance
m_P - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
number P of instances to re-sample per class label
m_samplingTime_ms - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
stores the time spent (milliseconds) in sammpling the new instances
m_seed - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
seed use for numbers generation
m_statisticsTime_ms - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
stores the time spent (milliseconds) in learning the distribution
m_totalInstancesPerClass - Variable in class weka.filters.supervised.instance.DistributionBasedBalance
used when MULTINOMIAL_BALANCE is selected
main(String[]) - Static method in class weka.filters.supervised.instance.DistributionBasedBalance
Main method for running this filter.
MULTINOMIAL_BALANCE - Static variable in class weka.filters.supervised.instance.DistributionBasedBalance
learn and sample Multinomial Distribution

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