surrogate_modelling
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Rapid - I - RapidMiner
About: ELKI is a framework for implementing data-mining algorithms with support for index structures, that includes a wide variety of clustering and outlier detection methods. Changes: The full changelog is not yet up. Here is an excerpt of the new functions in 0.5.0 - further speed improvements - R-Tree flexibility: multiple new split strategies, bulk loaders, insertion strategies, so that ELKI can now do many R-Tree variations, including the original Guttman R-Tree, not only the R*-Tree. - K-Means flexibility: MacQueen and Lloyd style iterations along with various seeding strategies, including K-Means++ - VA-File (static only, not dynamic databases); partial-VA to come for 0.5.0 final?
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MLboost: Machine Learning boost library in Python. MLboost main goal is to speedup any Machine Learning projects by simplifying data preprocessing, features selection and data visualisation. Design by Machine Learning practitioners to let them do ML...;) About SourceForge.net: SourceForge.net is the world's largest provider of hosting for Open Source software development projects.
SourceForge.net: boost your Machine Learning projects - Project Web Hosting - Open Source Software
Shark Machine Learning Library
News We are very actively working on the release of Shark 3.0. For this, we are rewriting the whole library. Most of the work has been done, and we are aiming at releasing the library within the next three months. Stay tuned! We submitted a pre-release to the Open Source Software World Challenge 2011 and are happy to announce that this alpha release of Shark 3.0 has just won the Gold Prize !
In this release we made major improvements to the documentation of various classes and packages. We have improved the javadoc of a number of classes and we have added a quite a few new tutorials.
Java Machine Learning Library (Java-ML)
Surrogate model - Wikipedia, the free encyclopedia
A surrogate model is an engineering method used when an outcome of interest cannot be easily directly measured, so a model of the outcome is used instead. Most engineering design problems require experiments and/or simulations to evaluate design objective and constraint functions as function of design variables. For example, in order to find the optimal airfoil shape for an aircraft wing, an engineer simulates the air flow around the wing for different shape variables (length, curvature, material, ..). For many real world problems, however, a single simulation can take many minutes, hours, or even days to complete.
Surrogate models - What? Surrogate models are fast-running approximations of complex time-consuming computer simulations. Surrogate models are also known as response surface models (RSM), metamodels or emulators.