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This library implements persistent and consistent processing of feed data without making assumptions of a feed's structure or source. In this context a feed can represent any chain of data that can be implemented as the `FeedEndpoint` interface of the *feed-api* module.

Stochastice Performance Logic is a formalism for capturing performance assumptions. It is, for example, possible to capture assumption that newer version of a function bar is faster than the previous version or that library foobar is faster than library barfoo when rendering antialiased text. The purpose of this framework is to allow evaluation of SPL formulas inside Java applications.

Class for building and using a Complement class Naive Bayes classifier. For more information see: Jason D. Rennie, Lawrence Shih, Jaime Teevan, David R. Karger: Tackling the Poor Assumptions of Naive Bayes Text Classifiers. In: ICML, 616-623, 2003. P.S.: TF, IDF and length normalization transforms, as described in the paper, can be performed through weka.filters.unsupervised.StringToWordVector.

AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes. The resulting algorithm is computationally efficient while delivering highly accurate classification on many learning tasks. For more information, see G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning. 58(1):5-24.

Axis2 is an effort to re-design and totally re-implement both Axis/Java and (eventually) Axis/C++ on a new architecture. Evolving from the now standard "handler chain" model which Axis1 pioneered, Axis2 is developing a more flexible pipeline architecture which can yet be managed and packaged in a more organized manner. This new design acknowledges the maturing of the Web services space in terms of new protocols such as WS-ReliableMessaging, WS-Security and WS-Addressing that are built on top of the base SOAP system. At the time Axis1 was designed, while it was fully expected that other protocols such as WS-ReliableMessaging would be built on top of it, there was not a proper extension architecture defined to enable clean composition of such layers. Thus, one of the key motivations for Axis2 is to provide a clean and simple environment for like Apache Sandesha and Apache WSS4J to layer on top of the base SOAP system. Another driving force for Axis2 as well as the move away from RPC oriented Web services towards more document-oriented, message style asynchronous service interactions. The Axis2 project is centered on a new representation for SOAP messages called AXIOM (AXIs Object Model). AXIOM consists of two parts: a complete XML Infoset representation and a SOAP Infoset representation on top of that. The XML Infoset representation provides a JDOM-like simple API but is built on a deferred model via a StAX-based (Streaming API for XML) pull parsing API. A key feature of AXIOM is that it allows one to stop building the XML tree and just access the pull stream directly; thus enabling both maximum flexibility and maximum performance. This approach allows us to support multiple levels of abstraction for consuming and offering Web services: using plain AXIOM, using generated code and statically data-bound data types and so on. At the time of Axis1's design, RPC-style, synchronous, request-response interactions were the order of the day for Web services. Today service interactions are much more message -oriented and exploit many different message exchange patterns. The Axis2 engine architecture is careful to not build in any assumptions of request-response patterns to ensure that it can be used easily to support arbitrary message exchange patterns.