What Is Topological Data Analysis?

Written by Caitlin Davidson


Topological Data Analysis Defined

Topological data analysis (TDA) is a field of mathematics which deals with qualitative geometric features to analyze datasets. Simply, TDA is a collection of powerful tools that have the ability to quantify shape and structure in data to answer questions from the data’s domain. This is done by representing some aspect of the data structure in a simplified topological signature.

TDA combines algebraic topology and statistical learning to give a quantitative basis for the study of the “shape” of data. By analyzing and understanding the geometric structure of data, it helps give users insights into what is often large, incomplete and high-dimensional data.

One of the key messages around topological data analysis is that data has shape and the shape matters.

In Data Defined, we help make the complex world of data more accessible by explaining some of the most complex aspects of the field.

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