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"

An Interactive Approach to Understanding Unsupervised Learning Algorithms

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Customer Personality Analysis Using Clustering

Graph Agglomerative Clustering Library

🤖 AI-powered CLI for file reorganization. Runs fully locally — no data leaves your machine.

Build Agglomerative hierarchical clustering algorithm from scratch, i.e. WITHOUT any advance libraries such as Numpy, Pandas, Scikit-learn, etc.

Agglomerative hierarchical clustering in JavaScript

The project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and face lower risk by tempering potential losses when the market is down.

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

PCA. Clustering Algorithms. Business Analytics.

Customer Segmentation Using Unsupervised Machine Learning Algorithms

Supervised hierarchical clustering

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.

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.

Linkage Methods for Hierarchical Clustering

Clustering and recognition of faces in a photo album

Image Clustering by KMeans and agglomerative hierarchical clustering

Agglomerative based clustering on gene expression dataset

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

This repository contains a collection of fundamental topics and techniques in machine learning. It aims to provide a comprehensive understanding of various aspects of machine learning through simplified notebooks. Each topic is covered in a separate notebook, allowing for easy exploration and learning.

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

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.

implementation of agglomerative single linkage clustering with minimum spanning tree algorithm

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

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

Semantic text clustering using sentence embeddings and agglomerative clustering.

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

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