Alternating clustering and GAN-based imputation in a feedback loop yields more accurate missing-value recovery on heterogeneous data than single-distribution methods.
Journal of Computer and Communications12, 53–75 (2024)
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Imputation Meets Clustering: Exploiting Latent Subgroup Structure for Missing Data Recovery
Alternating clustering and GAN-based imputation in a feedback loop yields more accurate missing-value recovery on heterogeneous data than single-distribution methods.