Constrained density-based spatial clustering of applications with noise (DBSCAN) using hyperparameter optimization

implementation of the new proposed HCA-DBSCAN algorithm

Hypercube Accelerated DBSCAN

Customer Segmentation using kmeans, hc, dbscan and gmm

Customer Segmentation - KMeans, HC, DBscan 🛒👜👝🎒

An end-to-end Machine Learning pipeline to identify and predict 4 distinct retail customer personas. Features multi-model clustering (K-Means, HC, DBSCAN) and hyperparameter-tuned KNN classification.

This notebook explores clustering using synthetic datasets. It covers data generation (blobs, moons, circles), preprocessing with StandardScaler, Hierarchical Clustering on make_blobs with dendrogram visualization, and DBSCAN on make_moons and make_circles. Each clustering result is visualized, demonstrating algorithm performance on diverse data

No description available

This project aims to perform customer segmentation using various clustering techniques such as KMeans, Hierarchical Clustering (HC), and DBSCAN. The goal is to group customers based on similarities in their features, which can be incredibly valuable for targeted marketing, customer retention strategies, and overall business insights.

Tratamento de dados e teste com os algoritimos KMeans, Hierarchical Clustering, DBSCAN

Using HC and DBSCAN on a pretty popular Wholesale Retialer dataset

Hierarchical Clustering, K-Means Clustering and DBSCAN

No description available

Programa de fidelidade para um e-commerce multimarcas, identificando clientes valiosos através de clusterização (K-Means, GMM, HC, DBSCAN). O projeto inclui análise exploratória de dados e visualização dos resultados, utilizando um dataset do Kaggle sobre e-commerce.