A C++ implementation of simple k-means clustering algorithm.

A version of the K-Means Algorithm targeting the Capacitated Clustering Problem

Multithread open source application for k-means clustering, support really big files (lineCount <= 1000000000, dimensionsCount <=1000, centroids count <=1000)

Implementation of k-means algorithm using MPI and OpenMP

Let's get those centroids!

Implementation of various data mining algorithms in c++

Project for Parallel Computing course. Sequential and parallel implementations of K-Means algorithm in C++ with OpenMP and CUDA.

KMeans With OMP Parallelization

image processing

This repository contains an implementation of the K-Means Clustering algorithm using C++. The purpose of the algorithm is to partition a dataset into clusters, where each cluster is represented by its centroid. This implementation uses Tokura distance, a weighted Euclidean distance, to measure similarity between data points and centroids.

K-Means Algorithm implemented using sequential and parallel algorithms.

KMeans algo in GUI using FLTK library.

Clustering de datos

k-means implementation for 2D points data ( SDL )

k-means algo using single core

Parallel implementation of K-Means algorithm

Native C++ implementation of the k-means clustering algorithm

Unsupervised Learning Classification with K-Means

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