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arXiv · 2407.14166

On Maximum Entropy Linear Feature Inversion

Paul M Baggenstoss
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Abstract

We revisit the classical problem of inverting dimension-reducing linear mappings using the maximum entropy (MaxEnt) criterion. In the literature, solutions are problem-dependent, inconsistent, and use different entropy measures. We propose a new unified approach that not only specializes to the existing approaches, but offers solutions to new cases, such as when data values are constrained to [0, 1], which has new applications in machine learning.

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Paul M Baggenstoss. 2024-07-19. On Maximum Entropy Linear Feature Inversion. https://arxiv.org/abs/2407.14166

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