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

KMeans algo in GUI using FLTK library.

Implementation of k-means algorithm using MPI and OpenMP

Clustering de datos

Let's get those centroids!

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

KMeans With OMP Parallelization

Implementation of various data mining algorithms in c++

image processing

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

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

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-Client Algorithm implemented in C++: This program receives data using nlohmann JSON and establishes a connection to the server through sockets

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