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Tropical Geometric Tools for Machine Learning: the TML package

2023-09-03 · David Barnhill, Ruriko Yoshida, Georgios Aliatimis, Keiji Miura

In the last decade, developments in tropical geometry have provided a number of uses directly applicable to problems in statistical learning. The TML package is the first R package which contains a comprehensive set of tools and methods used for basic computations related to tropical convexity, visualization of tropically convex sets, as well as supervised and unsupervised learning models using the tropical metric under the max-plus algebra over the tropical projective torus. Primarily, the TML package employs a Hit and Run Markov chain Monte Carlo sampler in conjunction with the tropical metric as its main tool for statistical inference. In addition to basic computation and various applications of the tropical HAR sampler, we also focus on several supervised and unsupervised methods incorporated in the TML package including tropical principal component analysis, tropical logistic regression and tropical kernel density estimation.

📄 PDF Abstract BibTeX arXiv:2309.01082

Code (1)

barnhilldave/tml 공식 구현

Tasks

Density Estimation

Methods 이 논문이 사용한 방법론

Focus 설명 없음
Logistic Regression Logistic Regression, despite its name, is a linear model for classification rather than regression. Logistic regression is also known in the literature as logit regression,…

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