Production-ready K-Means clustering for Apache Spark with pluggable Bregman divergences (KL, Itakura-Saito, L1, etc). 6 algorithms, 740 tests, cross-version persistence. Drop-in replacement for MLlib with mathematically correct distance functions for probability distributions, spectral data, and count data.

Euclidean distance & signed distance transform for multi-label 3D anisotropic images using marching parabolas.

A small-scale flask server facial recognition system, using a pre-trained facenet model with real-time web camera face recognition functionality, and a pre-trained Multi-Task Cascading Convolutional Neural Network (MTCNN) for face detection and cropping.

统计分析课程实验作业/包含《统计分析方法》中因子分析，主成分分析，Kmeans聚类等典型算法的手写实现

Implementations of different algorithms for building Euclidean minimum spanning tree in k-dimensional space.

Eight Puzzle solver using BFS, DFS & A* search algorithms

This is the official code for 'Squeeze Every Bit of Insight: Leveraging Few-shot Models with a Compact Support Set for Domain Transfer in Object Detection from Pineapple Fields' and 'Simple Object Detection Framework without Training' project.

This project consists of implementations of several kNN algorithms for road networks (aka finding nearest points of interest) and the experimental framework to compare them from a research paper published in PVLDB 2016. You can use it to add new methods and/or queries or reproduce our experimental results.

A Java console application that implements the factionality of the knn algorithm to find the similarity between a new user with only a few non zero ratings of some locations, find the k nearest neighbors through similarity score and then predict the ratings of the new user for the non rated locations.

Python 3 library for Multi-Criteria Decision Analysis based on distance metrics, providing twenty different distance metrics.

Allows for calculation of many types of distance between points

Code repository for Adult Social Care Overview

This repository contains a Python implementation of a K-Nearest Neighbors (KNN) classifier from scratch. It's applied to the "BankNote_Authentication" dataset, which consists of four features (variance, skew, curtosis, and entropy) and a class attribute indicating whether a banknote is real or forged.

Clustered customers into distinct groups based on similarity among demographical and geographical parameters. Applied PCA to dispose insignificant and multi correlated variances. Defined optimal number of clusters for K-Means algorithm. Used Euclidian distance as a measure between centroids.

The N-puzzle is a sliding puzzle that consists of a frame of numbered square tiles in random order with one tile missing. The puzzle can be of any size, with the most common sizes being 3x3 and 4x4. The objective of the puzzle is to rearrange the tiles to form a specific pattern.

Graphql API to recommend tourist sites based on user search criteria using the Euclidean distance algorithm.

K-Means and Bisecting K-Means clustering algorithms implemented in Python 3.

TextureBasedImageRetriever a Content Based Image Retriever that focuses on texture. It implements the offline phase which is the calulation of descriptors of all images in the datasetn, and the online phase that return the n-similar images from dataset given an input image.

Hand Segmentation and Finger Counting with Convex Hull

Swipe Keyboard Translates Relative Coordinates Into a Character Path & Searches the Subsequence in a Word List Using Euclidean Distance