Integrating Unsupervised and Supervised ML Models for Analysis of Synthetic Data From VAE, GAN, and Clustering of Variables
Lakshmi Prayaga,
Krishna Devulapalli,
Chandra Prayaga
et al.
Abstract:Clustering of variables is a specialized approach for dimensionality reduction. This strategy is evaluated for data reduction with a Kaggle diabetes dataset. Since the original dataset is small, Generative Adversarial Networks (GAN) and Variational Autoencoders (VAE) are used to generate 100,000 records and tested for resemblance to the real data using standard statistical methods. VAE-data is more representative of the real data than GAN-data when analyzed using machine learning (ML) models. Applying Clusteri… Show more
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