IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks
IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks
Missing value imputation is a challenging and well- researched topic in data mining. In this paper, we propose IFGAN, a missing value imputation algorithm based on Feature- specific Generative Adversarial Networks (GAN). Our idea is intuitive yet effective: a feature-specific generator is trained to impute missing values, while a discriminator …