Search Results for "machine learning python" - Page 6

A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer...

This project develops a simple, fast and easy to use Python graph library using NumPy, Scipy and PySparse.

jFAN2 project develops a Java API to use a neural network (neuro-fuzzy) called FAN (Free Associative Neurons). Its an reprogramed version of jFAN "https://sourceforge.net/projects/jfan/".

3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM. Quick Start: "java -jar nen.jar"

OpenSkyNet - Moving towards a comprehensive artificial intelligence solution for game developers under the LGPL. The goals are to implement action selection solvers, robust steering behaviors (including pathfinding algorithms), and machine learning.

Artificial neural network with eigenfaces for face recognition

Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.

Neuroph OCR - Handwriting Recognition is developed to recognize hand written letter and characters. It's engine derived's from the Java Neural Network Framework - Neuroph and as such it can be used as a standalone project or a Neuroph plug in.

Neural - is neural network engine with object-oriented design. Features: - Supports: backpropogation, RPROP algorithms. - Flexible input/outputs framework. - Distributed calculations.

Computer System for Adaptive Intelligent Life :: seeks to create a software system that is capable of learning. The project's ultimate goal is to further the ability of software to both adapt to individual users, and to respond their needs.