Cluster weather using PCA & K-Means

A Python package for fast 1D clustering using a Rust binary. Prefer ckmeans to Jenks.

BICO is a fast streaming algorithm to compute coresets for the k-means problem on very large sets of points.

Source code of the paper "Min-Max-Jump distance and its applications."

A fraud detection (exploratory) project using machine learning algorithms over 11 million real transactions

This project demonstrates customer segmentation using K-Means clustering, a popular machine learning technique. By analyzing customer data, we group customers into distinct segments to better understand their behaviors and preferences. This segmentation can help businesses tailor their marketing strategies and improve customer satisfaction.

This repository contains ml model for applying k means clustering on college data

Customer Segmentation using R

Dominant Color Extraction for Image Segmentation

Part of my PhD thesis - a system for reconstruction of damaged AIS data, consisting of 3 stages: clustering, anomaly detection and prediction

Implementation of the FLS++ algorithm for K-Means clustering.

Алгоритмы распознавания образов

Implementation of k-means algorithm in C (standard C89/C90, K&R code style)

K-means color quantization

Analyzing chat messages in virtual services to identify opportunities for future automation and improve communication efficiency.

Data analysis, clustering algorithms and forecasting for the demand of medicines in french hospitals problem.

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

K-means clustering algorithm using MapReduce.

This is a computer vision project using python3 and conventional computer vision techniques to determine a relative distance between two points in a given scene. [DOCUMENTED]