Generalizing Clustering Inferences with ML Augmentation of Ordinal Survey Data
Bhupendera Kumar,
Rajeev Kumar
Abstract:In this paper, we attempt to generalize the ability to achieve quality inferences of survey data for a larger population through data augmentation and unification. Data augmentation techniques have proven effective in enhancing models' performance by expanding the dataset's size. We employ ML data augmentation, unification, and clustering techniques. First, we augment the \textit{limited} survey data size using data augmentation technique(s). Next, we carry out data unification, followed by clustering for infe… Show more
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