mlpack: a scalable C++ machine learning library
-
Updated
Oct 25, 2017 - C++
mlpack: a scalable C++ machine learning library
A fast K Nearest Neighbor library for low-dimensional spaces
Navigable Small World Graphs For Approximate Nearest Neighbors In Rust
Vantage Point Tree implementation in Python 🌳
Java WSDL-based SOAP web service with Springboot (Spring-WS, Contract first) and nearest neighbor search
Neighbor Search and Clustering for Vectors using Locality-sensitive hashing and Randomized Projection to Hypercube
KNN Is A Machine Learning Algorithm For Pattern Recognition That Finds The Nearest K Observations To Predict A Target.
Four core workers of shotit: watcher, hasher, loader and searcher.
An overview and analysis of structures optimized for nearest neighbour searches.
Raku package with algorithms for finding nearest neighbors for different sets of objects.
This repository explores two optimization algorithms: the Traveling Salesman Problem (TSP) and Nearest Neighbor Search (NNS). It features Jupyter notebooks implementing brute-force solutions to both problems, utilizing Euclidean distance calculations and path visualizations. Ideal for learning about algorithm efficiency and optimization techniques.
A project based off of the multiple vehicle routing problem with time windows and constraints.
An Android library in Java for solving the Capacitated Vehicle Routing Problem (CVRP). Features include nearest neighbor algorithm for route optimization and efficient storage of distance matrices. Simplify CVRP implementation and enhance routing efficiency with DSM Solver.
Generates efficient package delivery routes, employing the nearest neighbor algorithm for on-time deliveries. Features real-time tracking, dynamic rerouting, and scalable infrastructure.
The project implements an algorithm that finds the closest pair of points in a 2D screen using a time complexity of O(n log n). The algorithm is implemented in an iOS application using the MVC architectural pattern.
Python wrapper for Boost Geometry Rtree
Near neighbor searching and clustering using LSH
VectorizeDB is a database for vectorized data and metadata, allowing for fast similarity search and retrieval.
An image similarity search engine has been developed that finds images similar to the image selected by the user from the dataset provided by the user. The latent vectors of the images are generated by a CNN based autoencoder model. KNN is used to find images similar to the selected image. An image similarity search engine platform has been created
Add a description, image, and links to the nearest-neighbor-search topic page so that developers can more easily learn about it.
To associate your repository with the nearest-neighbor-search topic, visit your repo's landing page and select "manage topics."