Paper
21 April 2020 Fisher information for big and disparate data
Author Affiliations +
Abstract
The extraction of useful information from large, disparate, and heterogeneous data sets requires a good set of theoretical and computational tools. The methods based on the ideas of Information Geometry (IG) offer an understanding of the hidden patterns inherent in the data as well as help in their visualization. Fisher Information is such a tool. It has been used widely in many areas of social and economic research leading to an improved understand of trends and hidden patterns. Here we outline its usefulness in understanding large and disparate data sets.
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Vinod K. Mishra "Fisher information for big and disparate data", Proc. SPIE 11395, Big Data II: Learning, Analytics, and Applications, 113950R (21 April 2020); https://doi.org/10.1117/12.2564119
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KEYWORDS
Intelligence systems

Machine learning

Neural networks

Statistical analysis

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