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Baseline framework for ReST based application to standardize Request / Response Structure and basic error Handling. This is for SPring Boot 1.5. Spring Boot 2.0 has quite a bitof Package restructure, causing incompatibility.

Pips offers stream like data producers and consumer for data points. Considering the numerous great stream based libraries it is quite superfluous but still used in some of my projects.

This module provides connectors for building classifiers with arbitrary scripts. This was originally intended to be a connector to neural network libraries but is quite general. The way to use these connetors is to simply provide a path to a directory containing a train.* and classify.* script that will be called at the appropriate times.

Provides support for the sKWRL rule-based reasoning language. Rule programs can be uploaded and are evaluated in a forward chaining algorithm whenever a transaction commits. Since the reasoner evaluates rules directly on the database, reasoning is quite efficient.

Provides support for the sKWRL rule-based reasoning language. Rule programs can be uploaded and are evaluated in a forward chaining algorithm whenever a transaction commits. Since the reasoner evaluates rules directly on the database, reasoning is quite efficient.

While most bundles work quite find with the typical wrapped bundle code from poms/wrapped there are some special cases where it does not work this way. This parent contains all bundles which are not meant to be wrapped in the classical way, but require some additional, special work.

<p> This project offers Exceptions to be used in Java programs. Although their names sound silly, the exceptions themselves are quite usefull. </p> <p> Please refer to the <a href='/exceptions_overview.html'>exceptions overview</a> page for a summary of all available exceptions. </p>

Class implementing a HyperPipe classifier. For each category a HyperPipe is constructed that contains all points of that category (essentially records the attribute bounds observed for each category). Test instances are classified according to the category that "most contains the instance". Does not handle numeric class, or missing values in test cases. Extremely simple algorithm, but has the advantage of being extremely fast, and works quite well when you have "smegloads" of attributes.

This module groups all different output writers. Different output writers have different dependencies. To ensure that those dependencies do not leak to other output writer, or that we can limit to number of dependencies at runtime, output writers are split into separate modules based on the dependencies they use. For example, the CloudWatch output writers depends on the AWS SDK, which is quite large and not used by any other output writer. If you only want to send metrics to Graphite, there should be no need to have the AWS SDK in your classpath at runtime. Some dependencies are also problematic. They can introduce incompatibilities. For example, a few writers are based directly on log4j or logback. This direct dependence breaks the use of SLF4J. By isolating those output writers to a specific module, we can ensure this has minimal impact.