Clustering Algorithms and their Application to Facial Image Analysis

Linkage Methods for Hierarchical Clustering

Offline and online (i.e., real-time) annotated clustering methods for text data.

This case requires to develop a customer segmentation to understand customer's behaviour and separate them in different groups according to their preferences, and once the division is done, this information can be given to marketing team so they can plan the strategy accordingly.

implementation of agglomerative single linkage clustering with minimum spanning tree algorithm

Design of OpenMP-based Parallel Dynamic Louvain algorithm for community detection.

Explores information retrieval techniques.

Design of OpenMP-based Parallel Louvain algorithm for community detection.

Comparison of K-Means and Agglomerative Clustering

Data mining and knowledge discovery from social media : implementation data analysis methods on data collection from Twitter

Agglomerative clustering algorithm in C++

codes to cluster stocks into groups based on value at risk using K-Means, Agglomerative, and GMM.

customer segmentation by rfm analysis

Credit Card Customer Segmentation using Agglomerative, K-Means, & K-Medoids

Given a dataset with different features for different countries, implementing a clustering algorithm to find groups of countries based on the given features using R

Performing basic clustering on a seeds dataset.

This is a homework about Clustering for machine learning course @ FUM.

Clustering with Agglomerative and DBSCAN algorithm Machine Learning

Python implementation of Agglomerative Clustering algorithm for unsupervised learning. Hierarchical clustering method that merges similar clusters iteratively. Suitable for various data types and shapes, offering insights into hierarchical structures within datasets.