C&EN

Illuminating the Interface of Blocc Chemistry and Data Science: An Introduction to K-Nearest Neighbor Analysis and K-Medoids Clustering

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The discovery of functional small molecules, chemical matter ...
SciELO

Machine learning classification based on k-Nearest Neighbors for PolSAR data

In this work, we focus on obtaining insights of the performances of some well-known machine learning image classification techniques (k-NN, Support Vector Machine, randomized decision tree and one ...
Frontiers

Density peak clustering algorithm based on weighted mutual K-nearest neighbors

1 School of Computer Science and Technology, Yibin University, Yibin, China 2 School of Computer and Software, Southwest Petroleum University, Chengdu, China Ever since Density Peak Clustering (DPC) ...
GitHub

Approximate Sparse Nearest-Neighbor Search in OpenSearch

Since version 2.11, OpenSearch has supported neural sparse retrieval as a novel semantic search approach. Leveraging inverted index technology, this method achieves efficiency comparable to ...
IEEE

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

Abstract: The K-nearest neighbors (kNNs) 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 ...
Visual Studio Magazine

Implementing k-NN Classification Using C#

Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to ...
Scientific Research Publishing

Zhu, Z. and Nandi, A.K. (2014) Automatic Modulation Classification: Principles, Algorithms and Applications. Wiley.

ABSTRACT: In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition ...