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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 implemented allows ... [More]
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]
Accord.NET Framework is a C# framework which extends the excellent AForge.NET Framework with new tools and libraries. The framework is comprised by libraries and sample applications demonstrating their features. Some of the libraries include: Accord.Statistics - library with statistical ... [More]
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. It's the Swiss army knife for machine learning and neural networking.
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]
The aim of this project is to implement a realistic application of artificial neural networks. Our work will be based on wisconsin breast cancer database (http://mlearn.ics.uci.edu/databases/breast-cancer-wisconsin/) and use the C++-based Torch machine learning library to implement BackPropagation ... [More]
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