A Python nearest neighbor descent for approximate nearest neighbors

Structural Deep Clustering Network

Fast k-NN graph construction for slow metrics

Efficient approximate k-nearest neighbors graph construction and search in Julia

Spark algorithms for building k-nn graphs

C++/Python implementation of Nearest Neighbor Descent for efficient approximate nearest neighbor search

Integration with (approximate) nearest neighbors libraries for scikit-learn + clustering based on with kNN-graphs.

A GPU (CUDA) implementation, with a python interface, of the approximated KNN graph computation with Random Sample Forest algorithm KNN.

Graph construction using Non Negative Kernel regression

Fruit data with Colours

Creation of an approximate kNN graph for diffusion application

Graph construction from data using Non Negative Kernel Regression

Problems Identification: This project involves the implementation of efficient and effective KNN classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

Official implementation of 'SP$^2$OT: Semantic-Regularized Progressive Partial Optimal Transport for Imbalanced Clustering'.

Generating KNN Graph and mutual KNN graph for a given data

🏫 [CS416] Special project

A simple implementation of kNN / k nearest neighbour classification algorithm for demonstration purposes only.