agglomerative-clustering

A Python implementation of divisive and hierarchical clustering algorithms. The algorithms were tested on the Human Gene DNA Sequence dataset and dendrograms were plotted.

The source code for our work "Towards better Validity: Dispersion based Clustering for unsupervised Person Re-identification"

Graph Agglomerative Clustering Library

An Interactive Approach to Understanding Unsupervised Learning Algorithms

A machine learning clustering model for customer segmentation to define marketing strategy.

PCA. Clustering Algorithms. Business Analytics.

Clustering Algorithms based on centroids namely K-Means Clustering, Agglomerative Clustering and Density Based Spatial Clustering

Supervised hierarchical clustering

Clustering Analysis Performed on the Customers of a Mall based on some common attributes such as salary, buying habits, age and purchasing power etc, using Machine Learning Algorithms.

This notebook will walk through some of the basics of Agglomerative Clustering.

Comparison of K-Means and Agglomerative Clustering

implementation of agglomerative single linkage clustering with minimum spanning tree algorithm

Agglomerative hierarchical clustering in JavaScript

Linkage Methods for Hierarchical Clustering

A search engine built to retrieve geographical information of any country.

Image Clustering by KMeans and agglomerative hierarchical clustering

A machine learning based log analysis to identify anomalous behaviour and act as Intrusion Detection System

CONTAINS CLUSTERING ALGORITHMS

Customer Personality Analysis is a detailed analysis of a company’s ideal customers. It helps a business to better understand its customers and makes it easier for them to modify products according to the specific needs, behaviors, and concerns of different types of customers. Customer personality analysis helps a business to modify its product based on its target customers from different types of customer segments. For example, instead of spending money to market a new product to every customer in the company’s database, a company can analyze which customer segment is most likely to buy the product and then market the product only on that particular segment.

Comparison of different linkages like complete, averagem ward on different datasets by plotting data on 2D plane by matplotlib

Introduction to Geospatial Data in Python using Google API and GeoPandas

This Repository Contains Different Machine Learning and Important Concepts

Assignment-07-Clustering-Hierarchical-Airlines. Perform clustering (hierarchical) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. Data Description: The file EastWestAirlinescontains information on passengers who belong to an airline’s frequent flier program. For each passenger the data include information on their mileage history and on different ways they accrued or spent miles in the last year. The goal is to try to identify clusters of passengers that have similar characteristics for the purpose of targeting different segments for different types of mileage offers.

Using Machine Learning to find people with similar personalities & interest for matchmaking

This project shows how to perform customers segmentation using Machine Learning algorithms. Three techniques will be presented and compared: KMeans, Agglomerative Clustering ,Affinity Propagation and DBSCAN.

Different clustering and clustering metrics are implemented in this repository

Graph Clustering using different techniques. [Node2vec, GraphSAGE, Agglomerative]