目标是提供一个完整的Java机器学习(Machine Learning/ML)框架,作为人工智能在学术界与工业界的桥梁. 让相关领域的研发人员能够在各种软硬件环境/数据结构/算法/模型之间无缝切换. 涵盖了从数据处理到模型的训练与评估各个环节,支持硬件加速和并行计算,是最快最全的Java机器学习库.

PH-Tree

Iterative k-dimensional tree implementation

Java project using a KD-Tree in CIE LAB color space to efficiently find the nearest color match from a CSV dataset.

A program that implements the (K-) Nearest Neighbour method and evaluates data

Traveling Salesman Problem (TSP).

Resize interpolations nearest neighbor and bilinear, 2nd semester, 6th exercise, digital media.

This project extends a custom-built singly linked list, transforming it into a powerful tool for complex data manipulation and algorithmic problem-solving. It introduces a suite of advanced methods for comparing, combining, and filtering tours, highlighted by the implementation of a route-optimization algorithm.

Finding nearest city to a position in android using k-d trees

Traveling Salesman Problem Solver using Nearest Neighbor and 2-OPT Algorithm.

Some basic classification methods (Naive Bayes, Decision Trees, Nearest Neighbour, Perceptrons) implemented from scratch in Java