Ball mapper: a shape summary for topological data analysis
Pawe{\l} D{\l}otko
TL;DR
This paper introduces a new shape descriptor inspired by the mapper algorithm for topological data analysis, enhancing exploratory data analysis capabilities.
Contribution
The paper presents a novel mapper-inspired shape descriptor that extends topological data analysis beyond existing tools.
Findings
Provides a new shape summary method for data analysis
Enhances the toolkit for topological data exploration
Applicable to various data types for shape summarization
Abstract
Topological data analysis provides a collection of tools to encapsulate and summarize the shape of data. Currently it is mainly restricted to \emph{mapper algorithm} and \emph{persistent homology}. In this paper we introduce new mapper--inspired descriptor that can be applied for exploratory data analysis.
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Taxonomy
TopicsTopological and Geometric Data Analysis · Data Management and Algorithms · Image Retrieval and Classification Techniques