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, coding process, and practical examples to help you understand how KNN works ...
The New York Times

I’m Building an Algorithm That Doesn’t Rot Your Brain

Mr. Conte is the co-founder and chief executive of Patreon. The World Wide Web was introduced some three decades ago. Describing in 2019 the hopes that had been projected onto the internet at its ...
Frontiers

Network intrusion detection based on relative mutual K-nearest neighbor density peak clustering

1 Yibin University, School of Computer Science and Technology, Yibin, China 2 Southwest Petroleum University, School of Computer and Software, Chengdu, China Network security is the core guarantee for ...
IEEE

K-Nearest Neighbor Algorithm Based on the Framework of Ordered Pair of Normalized Real Numbers

Abstract: The K-Nearest Neighbors (kNN) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
Frontiers

Fault diagnosis algorithm based on multi-channel neighbor feature convolutional network

Introduction: The health status of bearings is an essential prerequisite to ensure the safe and stable operation of vehicles. However, the negative impact of covariate shifts among data channels on ...
Scientific Research Publishing

Tang, Y., Chang, Y. and Li, K. (2023) Applications of K-Nearest Neighbor Algorithm in Intelligent Diagnosis of Wind Turbine Blades Damage. Renewable Energy, 212, 855-864.

ABSTRACT: To ensure the efficient operation and timely maintenance of wind turbines, thereby enhancing energy security, it is critical to monitor the operational status of wind turbines and promptly ...
GitHub

k-Nearest_Neighbour_algorithm.py

3. Write a program to implement the k-Nearest Neighbour algorithm to classify the iris to predict correct and wrong predictions. Use Python ML library classes for the prediction.
Scientific Research Publishing

A Comparison of Global Nearest Neighbor and Linear Assignment Problem Solution Methods on a Model Tracking Problem ()

In this paper we compare track data association purity, accuracy, and timing on a simple, idealized model tracking problem for two data association methods: Global Nearest Neighbor (GNN) and Linear ...