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Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al. (2007). This implementation globally replaces all missing values and transforms nominal attributes into binary ones. It also normalizes all attributes, so the coefficients in the output are based on the normalized data. Can either minimize the hinge loss (SVM) or log loss (logistic regression). For more information, see S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.

DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examples. Comprehensive experiments have demonstrated that this technique is consistently more accurate than the base classifier, Bagging and Random Forests. Decorate also obtains higher accuracy than Boosting on small training sets, and achieves comparable performance on larger training sets. For more details see: P. Melville, R. J. Mooney: Constructing Diverse Classifier Ensembles Using Artificial Training Examples. In: Eighteenth International Joint Conference on Artificial Intelligence, 505-510, 2003; P. Melville, R. J. Mooney (2004). Creating Diversity in Ensembles Using Artificial Data. Information Fusion: Special Issue on Diversity in Multiclassifier Systems.

TagSoup is a SAX-compliant parser written in Java that, instead of parsing well-formed or valid XML, parses HTML as it is found in the wild: poor, nasty and brutish, though quite often far from short. TagSoup is designed for people who have to process this stuff using some semblance of a rational application design. By providing a SAX interface, it allows standard XML tools to be applied to even the worst HTML. TagSoup also includes a command-line processor that reads HTML files and can generate either clean HTML or well-formed XML that is a close approximation to XHTML.

XBIS is an encoding format for XML documents that is fully convertible to and from text, with information set equivalence between the original document text and regenerated document text. It's intended for use in transmitting XML documents between application components, and is therefore designed for processing speed. The current Java language implementation offers several times the performance of SAX2 parsers working from text documents across a wide range of document types and sizes, and across JVMs tested, while also providing a substantial reduction in document size for most types of XML documents.

StringTemplate is a java template engine for generating source code, web pages, emails, or any other formatted text output. StringTemplate is particularly good at multi-targeted code generators, multiple site skins, and internationalization/localization. It evolved over years of effort developing jGuru.com. StringTemplate also generates the stringtemplate website: http://www.stringtemplate.org and powers the ANTLR v3 code generator. Its distinguishing characteristic is that unlike other engines, it strictly enforces model-view separation. Strict separation makes websites and code generators more flexible and maintainable; it also provides an excellent defense against malicious template authors. There are currently about 600 StringTemplate source downloads a month.