/Clustering-Systems

A repo of clustering systems

Primary LanguagePython

Clustering Systems

This repository contains implementations of K-Means Clustering and Hierarchical Clustering.

K-Means

Hierarchical Clustering

The current hierarchical clustering algorithms uses agglomeration and division to create the clusters and uses the following linkages:

  1. Single Link (MIN)
  2. Complete Link (MAX)
  3. Group Average (AVG)

The agglomerative hierarchical clustering script is divided into two classes:

  1. Agglomerative_Hierarchical
  2. Proximity_Matrix
  3. Divisive_Hierarchical

Results

The algorithms were run on a dataset consisting of amino acid sequences. The results are published as dendrograms:

K-Means Clustering

The K-means algorithm currently clusters the sequences into 311 clusters.

Hierarchical clustering:

  1. Single Link

Single Link

  1. Complete Link

Complete Link

  1. Group Average

Group Average

  1. DIANA

DIANA

Libraries Used

  1. Numpy
  2. Scipy
  3. Matplotlib

Authors

Naren Surampudi
![Aditya Srikanth]
![Prateek Das Gupta]