scikit-learn is a Python module integrating various machine learning algorithms under a common interface. It offers a wide range of methods such as Support Vector Machines, linear models (L1, L2 penalized), logistic regression, gaussian mixture models and more. The large number of algorithms aleady
... [More] implemented allows for easy comparison of accuracy and performance of various algorithms. [Less]
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications. A comprehensive set
... [More] of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details. [Less]
The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic interface for SVMs, features several SVM and kernel implementations, includes LinAdd optimizations and also Multiple Kernel Learning algorithms.
... [More] SHOGUN also implements a number of linear methods. It allows the input feature-objects to be dense, sparse or strings and of type int/short/double/char. It provides efficient implementations several kernels but also linear methods, hidden markov models etc. and interfaces to matlab,octave,python,R and has a cmdline interface and allows C++ extensions via a library. [Less]
PyBrain is a modular Machine Learning Library for Python. It's goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms.
PyBrain is short for Python-Based Reinforcement Learning
... [More], Artificial Intelligence and Neural Network Library.
It's the Swiss army knife for machine learning and neural networking. [Less]
Coeval is a free Corpus Evaluation software written in Java.It allows you to create, manage and customize your own corpus of documents.
Coeval can be used to train classifiers, evaluate performance and cross-compare classifiers on the same corpus.
A Support Vector Machine classifier (LIBSVM --
... [More] A Library for Support Vector Machines) is provided with this release and it also allows you easily add and test out your classifiers.
RequirementsApache Tomcat 6.x MySQL 5.1 Java EE 5 Eclipse 3.x Instructionsopen mysql command line, type and execute "source COEVAL_HOME/db/dump.sql" edit COEVAL_HOME/WEB-INF/mysql.properties with your mysql account data edit COEVAL_HOME/localhost.properties with your Apache Tomcat account data load with ant "build.xml" and deploy Coeval Contact MePlease feel free to contact me if you have any questions or comments. [Less]