Recognizing Variables from their Data via Deep Embeddings of Distributions
Abstract
A key obstacle in automated analytics and meta-learning is the inability to recognize when different datasets contain measurements of the same variable. Because provided attribute labels are often uninformative in practice, this task may be more robustly addressed by leveraging the data values themselves rather than just relying on their arbitrarily selected variable names. Here, we present a computationally efficient method to identify...
Paper Details
Title
Recognizing Variables from their Data via Deep Embeddings of Distributions
Published Date
Sep 11, 2019
Journal
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