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]
Modular toolkit for Data Processing is a library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. Implemented algorithms include PCA,ICA,SFA, and many more.
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