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 Louvain algorithm for community detection.

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

Explores information retrieval techniques.

Comparison of K-Means and Agglomerative Clustering

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

📊 Analyze mall customers through machine learning to discover key segments by age, income, and spending, enhancing targeted marketing and revenue.

Applying various clustering methods on ORL dataset with post processing enhancement

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

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.

customer segmentation by rfm analysis

Agglomerative clustering algorithm in C++

A comparative machine learning pipeline evaluating K-Means, Agglomerative Hierarchical, and HDBSCAN clustering on the Iris dataset.

Customer segmentation and purchasing behaviour analysis for a marketing campaign using data mining techniques.

Implementation of an agglomerative clustering algorithm.