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.
Keywords
tropical machine learning, tropical geometry, tropical data
science