There are 2 repositories under density-based-clustering topic.
Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms - R package
Python implementation of Density-Based Clustering Validation
Distance-based Analysis of DAta-manifolds in python
Semi-Supervised Density Peak Clustering Algorithm, Incremental Learning, Fault Detection(基于半监督密度聚类+增量学习的故障诊断)
Fast variant of Density Peaks clustering
A Python package for common-nearest-neighbours clustering
Density-Based Clustering Validation
Clustering Algorithms based on centroids namely K-Means Clustering, Agglomerative Clustering and Density Based Spatial Clustering
Colelction of various clustering algorithms including K means, HAC, DBscan. Also includes Hadoop, MapReduce, implementation of K mean algorithm
MATLAB implementation of the RNN-DBSCAN clustering algorithm
"Enhancing In-Tree-based Clustering via Distance Ensemble and Kernelization", Teng Qiu, Yongjie Li, in Pattern Recognition, 2020.
We proposes a novel and robust 3D object segmentation method, the Gaussian Density Model (GDM) algorithm. The algorithm works with point clouds scanned in the urban environment using the density metrics, based on existing quantity of features in the neighborhood. The LiDAR Velodyne 64E was used to scan urban environment.
A rust library inspired by kDDBSCAN clustering algorithm
CSE601 Course Projects - Fall 2017
A new density-based clustering algorithm for data with arbitrary shapes and densities
A new clustering algorithm using local gap density
New York crime analysis - R - Data mining course - association rules - density clustering(DBSCAN) - hotspots detection - mapping crimes
CSE 601 Data mining and bioinformatics
Local Outlier Factor (LOF), a density-based outlier detection technique to find frauds in credit card transactions.
Machine Learning course project (3rd-year B.tech. CSE)
A Parallel Graph Partitioning Approach designed to work on density-based clustering algorithms.
Space Breakdown Method (SBM) is a clustering algorithm developed for Spike Sorting handling overlapping and imbalanced data. Improved Space Breakdown Method (ISBM) is the updated and improved version of SBM. A new algorithm for the detection of brain oscillations packets has been developed based on SBM, called Time-Frequency Breakdown Method (TFBM)
Density based clustering
Analysis of when and where New York City (NYC) vehicle collisions occur with a focus on collisions involving pedestrians and cyclists.
Use DBSCAN to cluster a couple of datasests. Examine how changing its parameters (epsilon and min_samples) changes the resulting cluster structure.
R & Python | Unsupervised Learning Project
Implemented various clustering algorithms such as k-means, k-means++, hierarchical clustering, and DBSCAN to segment mall customers based on their spending behavior and demographics.
analyze the shopping behaviors and demographic profiles of customers visiting a mall using various clustering techniques.