TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
Scientific Research Publishing

Larose, D.T. and Larose, C.D. (2014) k-Nearest Neighbor Algorithm.

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...
Visual Studio Magazine

Implementing k-Nearest Neighbors Regression Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of k-nearest neighbors regression using JavaScript. There are many machine learning regression techniques, but k-nearest neighbors is ...
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 ...
GitHub

knearest-neighbor-algorithm

This project demonstrates how to implement the K-Nearest Neighbors (KNN) algorithm for classification on a customer dataset. The program iterates through different values of k (number of neighbors) ...
Scientific Research Publishing

Shi, M., Ling, Z. and Zu, J. (2003) Association Using Modified Global Nearest Neighbor in the Presence of Bias.

ABSTRACT: 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 ...
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 ...