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 ...
GitHub

knnpe: A Python package implementing the k-nearest neighbor permutation entropy

L. G. J. M. Voltarelli, A. A. B. Pessa, L. Zunino, R. S. Zola, E. K. Lenzi, M. Perc, H. V. Ribeiro, Characterizing unstructured data with the nearest neighbor ...
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 ...
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 ...
Frontiers

Random kernel k-nearest neighbors regression

The k-nearest neighbors (KNN) regression method, known for its nonparametric nature, is highly valued for its simplicity and its effectiveness in handling complex structured data, particularly in big ...
Frontiers

Optimization of the k-nearest-neighbors model for summer Arctic Sea ice prediction

The Arctic sea ice plays a significant role in climate-related processes and has a considerable effect on humans, however accurately predicting the Arctic sea ice concentration is still challenging.
IEEE

Hybrid Genetic Algorithm With k-Nearest Neighbors for Radial Distribution Network Reconfiguration

Abstract: Distribution network reconfiguration (DNR) is to control switches to reduce system losses, alleviate overloads, and mitigate voltage fluctuations. DNR is challenging due to nonlinear power ...