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This package contains a classifier that can be used to train a two-class kernel logistic regression model with the kernel functions that are available in WEKA. It optimises the negative log-likelihood with a quadratic penalty. Both, BFGS and conjugate gradient descent, are available as optimisation methods, but the former is normally faster. It is possible to use multiple threads, but the speed-up is generally very marginal when used with BFGS optimisation. With conjugate gradient descent optimisation, greater speed-ups can be achieved when using multiple threads. With the default kernel, the dot product kernel, this method produces results that are close to identical to those obtained using standard logistic regression in WEKA, provided a sufficiently large value for the parameter determining the size of the quadratic penalty is used in both cases.

Siena is a persistence abstraction layer made in Java with various implementations: * siena-jdbc: persists objects into a relational database using JDBC (status: deeply tested) * siena-gae: persists objects into the Google App Engine's datastore using its low-level API (status: beta) * siena-sdb: persists objects using Amazon's SimpleDB (very experimental) * siena-remote: persists objects remotely using a remote web application that uses siena. (planning) Siena is also: * Intrusive. You make a class persistent by extending a certain class. Relationships are defined also in an intrusive way. * Simple. Simplicity is the most important thing. * Limited. Due to the simplicity there are several unsupported things such as JOINs. * Extensible. There are two interfaces you can implement on your own way.

JavaCL is an Object-Oriented API that makes the C OpenCL API available to Java in a very natural way. It hides away the complexity of cross-platform C bindings, has a clean OO design (with generics, Java enums, NIO buffers, fully typed exceptions...), provides high-level features (OpenGL-interop, array reductions) and comes with samples and demos. For more info, please visit http://code.google.com/p/nativelibs4java/wiki/OpenCL.

JavaCL is an Object-Oriented API that makes the C OpenCL API available to Java in a very natural way. It hides away the complexity of cross-platform C bindings, has a clean OO design (with generics, Java enums, NIO buffers, fully typed exceptions...), provides high-level features (OpenGL-interop, array reductions) and comes with samples and demos. For more info, please visit http://code.google.com/p/nativelibs4java/wiki/OpenCL.

YET ANOTHER IMPLEMENTATION OF LEVENSHTEIN DISTANCE GenericLevenshtein is an implementation of Minimum Edit Distance, also called Levenshtein Distance, written by Ramon Ziai and Niels Ott. This algorithm is very popular and it is often used to compute the similarity of strings. The difference in the presented implementation is that it can operate on sequences of any Java object implementing equals(Object). So no matter if you want to compare genome sequences or sequences of numbers, or just strings, here you go! Furthermore, the costs of the replace, insert, and delete operations can be customized by implementing the simple WeightCalculator<T> interface. In that case it is not a requirement to rely on equals(Object) as your implementation can do whatever you like it to do in oder to compare objects.

Kanbanery (https://kanbanery.com) is a simple but powerful Agile project management system, to be precise it focuses around the idea of Kanban, a somewhat near idea to SCRUM but with less strict rules. The heart of each Kanban flow is the Kanban board, IceBox and Archive - there are all easy accessible via this API. Janbanery wraps around the RESTful API delivered by Kanbanery while adding some more features like mass operations or filtering of results. In the end, it's very easy and pleasant to implement your own Kanbanery client be it on the desktop, mobile (android) or as for example Gradle / SBT script to take full advantage of kanbanery's features.

Kanbanery (https://kanbanery.com) is a simple but powerful Agile project management system, to be precise it focuses around the idea of Kanban, a somewhat near idea to SCRUM but with less strict rules. The heart of each Kanban flow is the Kanban board, IceBox and Archive - there are all easy accessible via this API. Janbanery wraps around the RESTful API delivered by Kanbanery while adding some more features like mass operations or filtering of results. In the end, it's very easy and pleasant to implement your own Kanbanery client be it on the desktop, mobile (android) or as for example Gradle / SBT script to take full advantage of kanbanery's features.