VAE-Inf trains a VAE on majority data to build a reference distribution, then uses limited minority samples and a projection score to produce classifiers with guaranteed control of false-positive rates in imbalanced settings.
The minority-class proportion is defined asρ=N2/(N1 +N 2)
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VAE-Inf: A statistically interpretable generative paradigm for imbalanced classification
VAE-Inf trains a VAE on majority data to build a reference distribution, then uses limited minority samples and a projection score to produce classifiers with guaranteed control of false-positive rates in imbalanced settings.