Topological Data Analysis: An Overview

Abstract

A growing area of mathematics topological data analysis (TDA) uses fundamental concepts of topology to analyze complex, high-dimensional data. A topological network represents the data, and the TDA uses the network to analyze the shape of the data and identify features in the network that correspond to patterns in the data. These patterns extract knowledge from the data. TDA provides a framework to advance machine learnings ability to understand and analyze large, complex data. This paper provides background information about TDA, TDA applications for large data sets, and details related to the investigation and implementation of existing tools and environments.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2021
Accession Number
AD1136048

Entities

People

  • Amy E. Bednar

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Autonomy
  • Engineered Resilient Systems

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  • Abstracts
  • Algorithms
  • Big Data
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  • Data Analysis
  • Data Sets
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  • Topology
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Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML