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, ...
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 ...
Frontiers

A fashion product recommendation based on adaptive VPKNN-NET algorithm without fuzzy similar image

1 Department of Computer Science, Madurai Kamaraj University, Madurai, Tamil Nadu, India 2 P.G. Department of Computer Science, Government Arts and Science College, Madurai, Tamil Nadu, India ...
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 ...
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 ...