Deep Learning with Yacine on MSN

Build k-nearest neighbors from scratch in Python – step by step tutorial

Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, ...
IEEE

A Topological-Indicators-Based k-Means Clustering Algorithm and Its Application in Time Series Data: A Case Study on Sea Level Variability in Peninsular Malaysia

Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
Frontiers

Efficient vegetation filtering method using K-means clustering algorithm: case study of high steep rock slope

Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...
IEEE

Efficient Hardware Architecture Design of K-Means Clustering Algorithm for AV1 Palette Mode Coding

Abstract: The palette mode is a specialized coding tool for coding screen content video in Alliance for Open Media Video 1 (AV1), and K-means clustering is a necessary step in the palette mode.
Scientific Research Publishing

Ikotun, A. M., Ezugwu, A. E., Abualigah, L., Abuhaija, B., & Heming, J. (2023). K-means Clustering Algorithms: A Comprehensive Review, Variants Analysis, and Advances in the ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...
GitHub

A k-MLE framework with its k-VARs algorithm for multivariate time-series clustering

/ or ROOT: the project root directory. expt_synthetic/: contains the scripts that simulate data and perform benchmarks that appear in our manuscript. expt_wafer/: contains the scripts that applies our ...
Scientific Research Publishing

Gavin, L. (2016) Clustering Web Users with Streaming K-Means.

ABSTRACT: The use of machine learning algorithms to identify characteristics in Distributed Denial of Service (DDoS) attacks has emerged as a powerful approach in cybersecurity. DDoS attacks, which ...
GitHub

k-means-clustering

This project consists in the implementation of the K-Means and Mini-Batch K-Means clustering algorithms. This is not to be considered as the final and most efficient algorithm implementation as the ...