PyImageSearch

DECEMBER 23, 2024

Or think about a real-time facial recognition system that must match a face in a crowd to a database of thousands. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play. Imagine a database with billions of samples ( ) (e.g., Traditional exact nearest neighbor search methods (e.g.,

K-nearest Neighbors 112

K-nearest Neighbors Algorithm Deep Learning Deep Learning 112

Dataconomy

MARCH 4, 2025

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Association rule mining Association rule mining identifies interesting relations between variables in large databases.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

IBM Journey to AI blog

DECEMBER 20, 2023

Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others. They’re also part of a family of generative learning algorithms that model the input distribution of a given class or/category.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

PyImageSearch

JANUARY 27, 2025

Home Table of Contents Approximate Nearest Neighbor with Locality Sensitive Hashing (LSH) What Is Locality Sensitive Hashing (LSH)? Refinement: The candidate set is then refined by computing the actual distances between the query point and the candidates to find the approximate nearest neighbors. Download the code!

K-nearest Neighbors 92

K-nearest Neighbors Algorithm Data Preparation Database 92

Pickl AI

JULY 17, 2023

It aims to partition a given dataset into K clusters, where each data point belongs to the cluster with the nearest mean. K-NN (k nearest neighbors): K-Nearest Neighbors (K-NN) is a simple yet powerful algorithm used for both classification and regression tasks in Machine Learning.

Machine Learning 52

Machine Learning Machine Learning Clustering K-nearest Neighbors 52

AWS Machine Learning Blog

FEBRUARY 25, 2025

Instead of treating each input as entirely unique, we can use a distance-based approach like k-nearest neighbors (k-NN) to assign a class based on the most similar examples surrounding the input. To make this work, we need to transform the textual interactions into a format that allows algebraic operations.

Algorithm 77

Algorithm Machine Learning Machine Learning K-nearest Neighbors 77

AWS Machine Learning Blog

JANUARY 6, 2023

In this post, we present a solution to handle OOC situations through knowledge graph-based embedding search using the k-nearest neighbor (kNN) search capabilities of OpenSearch Service. Check out Part 1 and Part 2 of this series to learn more about creating knowledge graphs and GNN embedding using Amazon Neptune ML.

AWS 101

AWS ML ML Machine Learning 101