GitHub

A fast approximate nearest neighbor search library for Go

Hann is a high-performance approximate nearest neighbor search (ANN) library for Go. It provides a collection of index data structures for efficient similarity search in high-dimensional spaces.
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 ...
IEEE

Applying the K Nearest Neighbor algorithm (KNN) in a microwave filter

Abstract: this study introduces a novel approach employing the K-nearest neighbor (KNN) algorithm for designing a planar microwave filter. It explores the application of supervised machine learning ...
app.com

Neighbors over algorithms: Service Professionals show community commitment

“Customer looking to replace 20-year-old furnace. No heat. Can’t afford a new system. Needs help.”“Has been clogged for about a week; yesterday it started getting bad. We were out there about a month ...
Hosted on MSN

She confronted neighbors then they turned her into code compliance

Description: If you’re struggling, consider therapy with our sponsor BetterHelp. This is quite the Neighborhood feud. This Lady contacted us as she received a citation warning from code compliance but ...
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 ...