Download com.github.fracpete JAR files with all dependencies

The LaTeX Maven Plugin is useful for building a set of LaTeX documents.

LaTeX support for Maven projects

sizeofag is a Java Agent that allows you to determine the size of Java objects from within the JVM at runtime. This makes it very useful for developing Java frameworks that take memory constraints into account.

Virtual environment managment for Weka.

Allows recording of sound, webcam and screen to create screencasts, e.g., for YouTube.

Application for creating screencasts (desktop and webcam).

Tool for bootstrapping Maven applications by simply using a list of dependencies.

Library for reading/writing jsonlines data using the gson library under the hood for automatic deserialization/serialization of objects.

Maximum Likelihood Rule Ensembles (MLRules) is a new rule induction algorithm for solving classification problems via probability estimation. The ensemble is built using boosting, by greedily minimizing the negative loglikelihood which results in estimating the class conditional probability distribution. The main advantage of decision rules is their simplicity and comprehensibility: they are logical statements of the form "if condition then decision", which is probably the easiest form of model to interpret. On the other hand, by exploiting a powerful statistical technique to induce the rules, the final ensemble has very high prediction accuracy. Fork of the original code located at: http://www.cs.put.poznan.pl/wkotlowski/software-mlrules.html

Classifier (regression/classification) using the LightGBM gradient boosting framework (https://github.com/microsoft/LightGBM).