Topological Data Analysis – Persistent Homology
Sina Ghafouri
Ibn-Sina Multidisciplinary Lab,
Shahid Beheshti University
Abstract:
The amount of available data has increased dramatically
in recent years, and this situation necessitates the
development of innovative and efficient data-processing
methods.
Topological data analysis provides a set of tools to
characterize the shape of data, in terms of the presence
of holes or cavities between the points. The main tool is
persistent homology, an adaptation of homology to
point cloud data.
In this talk, we will see how persistent homology gives us
a new insight into the data by looking at it globally. and
also the meaning of persistence and how it works.