SHARK provides libraries for the design of adaptive systems, including methods for linear and nonlinear optimization (e.g., evolutionary and gradient-based algorithms), kernel-based algorithms and neural networks, and other machine learning techniques.
The Shark repository has moved:
- Shark repository moved: https://github.com/Shark-ML/Shark
- Completely rewritten library: http://image.diku.dk/shark
- Shark provides an excellent trade-off between flexibility as well as ease-of-use on the one hand and computational efficiency on the other.
- Shark offers numerous algorithms from various machine learning and computational intelligence domains in a way that they can be easily combined and extended.
- Shark comes with a lot of powerful algorithms that are to our best knowledge not implemented in any other library, for example in the domains of model selection and training of binary and multi-class SVMs, evolutionary single- and multi-objective optimization.
- License changed to more permissive LGPL
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