Search Results for "machine learning python" - Page 4

CompLearn is a general-purpose compression-based machine learning system that uses data compression to learn or data mine patterns in arbitrary data.

FLPD is an automatic learning system based on fuzzy prototypes, composed of a C++ library for machine learning and fuzzy logic and an experimentation framework.

The TreeQ package is a set of C-language applications that implement a automatic machine learning algorithm based on a tree-structured classifier. This approach is particularly effective for high-dimensional continuous data such as audio and video.

JUDGE (Java Utility for Document Genre Eduction) features automatic classification and clustering of documents, optionally as a webservice. The program is written entirely in Java and makes use of the Weka machine learning toolkit.

Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.

VFML -- Very Fast Machine Learning toolkit. A collection of tools, learners, and APIs for working with high-speed data streams and very large data sets.

Ruby SVM is a Ruby binding to the very popular and highly useful libsvm library (released under a seperate license) This allows you to effortlessly experiment with machine learning, in particular Support Vector Machines, in Ruby. SVM's have found use in

HORUS is a system for knowledge acquisition, hypothesis generation, inference and learning. It is an interactive, internet environment accessible to a diverse community of users (public-access or membership basis) - see also UMKAILASH project for more.

Weka-Parallel is a modification to Weka, created with the intention of being able to harness the power of Weka and the speed of parallel processing to be able to run a number of data mining and machine learning algorithms quickly.

Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.

...ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. Post analysis, the toolkit further automates building the visual representations for the trained model.

UGLi ML: The Undirected Graphical Library for Machine Learning. Easy, agile learning and inference from structured/relational data using Markov Networks and Conditional Random Fields.

R based genetic algorithm for optimization, variable selection and other machine learning and statistical analysis approaches.

Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.

ScenConnect shows scenarios as networks of situation and event tag sets, for fast comparisons. It links scenarios to tags, scores, and other metadata, creating situationals suitable for search, mining, machine learning, and planning.

In Green Cloud here is a central global server which does the work of global database management along with providing complex analysis services for the users (farmers, scientists) through the client machines and the public access web portal. The existing agricultural databases throughout the world can also be used for inference purposes and their data may also be updated by our server. The meteorological servers can be accessed for climate data.This server-client architecture mandatory in...