Nearest Point with Indexing Ratio (NPIR) tries to solve the clustering problem based on the nearest neighbor search technique by finding the nearest neighbors for the points that are already clustered based on the distance between them and cluster them accordingly. The algorithm does not consider all the nearest points at once to cluster a single point but iteratively considers only one nearest point based on an election operation using a distance vector. NPIR tries to solve some limitations of other clustering algorithms. It tries to cluster arbitrary shapes which have non-spherical clusters, clusters with unusual shapes, or clusters with different densities.

Team Members

Useful Links

• The source code of NPIR can be found on GitHub here
• The Google colab copy can be found here and here
• The documentation of the source code can be found here
• Live demo of NPIR can be found here
• Published Paper of NPIR can be found here

Published Paper

NPIR Description