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DKPro Lab is a lightweight framework for parameter sweeping experiments. It allows to set up experiments consisting of multiple interdependent tasks in a declarative manner with minimal overhead. Parameters are injected into tasks using via annotated class fields. Data produced by a task for any particular parameter configuration is stored and re-used whenever possible to avoid the needless recalculation of results. Reports can be attached to each task to post-process the experimental results and present them in a convenient manner, e.g. as tables or charts.

JAXB 2.1.x XJC Boolean-Getter Plugin This plugin causes getter methods for Boolean Objects to be called "getXX" instead of "isXX". Downloaded from http://fisheye5.atlassian.com/browse/~raw,r=1.1/jaxb2-commons/www/boolean-getter/index.html on 18/03/10 Yiannis Paschalidis Sanity4J was created to simplify running multiple static code analysis tools on the Java projects. It provides a single entry point to run all the selected tools and produce a consolidated report, which presents all findings in an easily accessible manner.

RBFNetwork implements a normalized Gaussian radial basisbasis function network. It uses the k-means clustering algorithm to provide the basis functions and learns either a logistic regression (discrete class problems) or linear regression (numeric class problems) on top of that. Symmetric multivariate Gaussians are fit to the data from each cluster. If the class is nominal it uses the given number of clusters per class. RBFRegressor implements radial basis function networks for regression, trained in a fully supervised manner using WEKA's Optimization class by minimizing squared error with the BFGS method. It is possible to use conjugate gradient descent rather than BFGS updates, which is faster for cases with many parameters, and to use normalized basis functions instead of unnormalized ones.