Bi-Discriminator Class-Conditional Tabular GAN

• URL: http://arxiv.org/abs/2111.06549v1
• Date: Fri, 12 Nov 2021 03:31:28 GMT
• Title: Bi-Discriminator Class-Conditional Tabular GAN
• Abstract summary: We introduce a bi-discriminator GAN for synthesizing datasets containing continuous, binary, and discrete columns. Our experimental results on four benchmarking public datasets corroborate the superior performance of our GAN.
• Score: 5.429166489331484
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: This paper introduces a bi-discriminator GAN for synthesizing tabular datasets containing continuous, binary, and discrete columns. Our proposed approach employs an adapted preprocessing scheme and a novel conditional term for the generator network to more effectively capture the input sample distributions. Additionally, we implement straightforward yet effective architectures for discriminator networks aiming at providing more discriminative gradient information to the generator. Our experimental results on four benchmarking public datasets corroborates the superior performance of our GAN both in terms of likelihood fitness metric and machine learning efficacy.

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