A Logifold Structure for Measure Space

In this paper, we develop a geometric formulation of datasets. The key novel idea is to formulate a dataset to be a fuzzy topological measure space as a global object and equip the space with an atlas of local charts using graphs of fuzzy linear logical functions. We call such a space a logifold. In applications, the charts are constructed by machine learning with neural network models. We implement the logifold formulation to find fuzzy domains of a dataset and to improve accuracy in data classification problems.

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Journal
Axioms
Published
2025-08-01
DOI
https://doi.org/10.3390/axioms14080599
Primary Topic
Topological and Geometric Data Analysis
Type
article
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article

A Logifold Structure for Measure Space

Siu-Cheong Lau, Inkee Jung
Axioms
Topological and Geometric Data Analysis
article

A Logifold Structure for Measure Space

Siu-Cheong Lau, Inkee Jung
article en

Abstract

In this paper, we develop a geometric formulation of datasets. The key novel idea is to formulate a dataset to be a fuzzy topological measure space as a global object and equip the space with an atlas of local charts using graphs of fuzzy linear logical functions. We call such a space a logifold. In applications, the charts are constructed by machine learning with neural network models. We implement the logifold formulation to find fuzzy domains of a dataset and to improve accuracy in data classification problems.

AxiomsVol. 14(8)
Boston University (US)
Openalex Percentile: Top 79%
Topological and Geometric Data Analysis
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