class EUS extends AnyRef
Evolutionary Under Sampling. Original paper: "Evolutionary Under-Sampling for Classification with Imbalanced Data Sets: Proposals and Taxonomy" by Salvador Garcia and Francisco Herrera.
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EUS(data: Data, seed: Long = System.currentTimeMillis(), populationSize: Int = 50, maxEvaluations: Int = 1000, algorithm: String = "EBUSMSGM", dist: Distance = Distance.EUCLIDEAN, probHUX: Double = 0.25, recombination: Double = 0.35, prob0to1: Double = 0.05, normalize: Boolean = false, randomData: Boolean = false, verbose: Boolean = false)
- data
data to work with
- seed
seed to use. If it is not provided, it will use the system time
- populationSize
number of chromosomes to generate
- maxEvaluations
number of evaluations
- algorithm
version of core to execute. One of: EBUSGSGM, EBUSMSGM, EBUSGSAUC, EBUSMSAUC, EUSCMGSGM, EUSCMMSGM, EUSCMGSAUC or EUSCMMSAUC
- dist
object of Distance enumeration representing the distance to be used
- probHUX
probability of changing a gen from 0 to 1 (used in crossover)
- recombination
recombination threshold (used in reinitialization)
- prob0to1
probability of changing a gen from 0 to 1 (used in reinitialization)
- normalize
normalize the data or not
- randomData
iterate through the data randomly or not
- verbose
choose to display information about the execution or not
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def
compute(): Data
Compute the EUS algorithm.
Compute the EUS algorithm.
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undersampled data structure
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