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This is a Quantitative Study study.

October 20, 2025Open Access

Multiscale 2-Mapper -- Exploratory Data Analysis Guided by the First Betti Number

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The study introduces a 2-Mapper algorithm that helps identify connectivity and clustering in data using topological tools.
Parameter selection is crucial; using persistent Betti-1 information enhances the effectiveness of the 2-Mapper approach.
The computational analysis focuses on how cover choice impacts the Multiscale Mapper, especially in three-dimensional data.
This method could improve interpretations in data science by leveraging topological structures, especially in complex shapes.

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Exploratory analysis reveals clustering and connectivity in data using 2-Mapper, suggesting optimized parameters based on Betti number.

Halley Fritze (2025) studied this question.

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