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Class implementing the predictive apriori algorithm for mining association rules. It searches with an increasing support threshold for the best 'n' rules concerning a support-based corrected confidence value. For more information see: Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence. In: 5th European Conference on Principles of Data Mining and Knowledge Discovery, 424-435, 2001.

JavaANPR is an automatic number plate recognition software, which implements algorithmic and mathematical principles from field of artificial intelligence, machine vision and neural networks. It was created by Ondrej Martinsky in 2006 and 2007 as part of the research plan "Security-oriented research in information technology, MSM 0021630528" at Brno University of Technology.

Jodd utility library

Each Java project should follow a given coding style. I.e., all contributions to the source code should use the same formatting rules, design principles, code patterns, idioms, etc. I published such a coding style in my GitHub project codingstyle (https://github.com/uhafner/codingstyle) - I am using this coding style in my lectures about software development at Munich University of Applied Sciences and in all of my open source projects. If you want to use this coding style as well, you can use this Maven POM as parent of your own POM. Then you get the configuration several static analysis and testing tools for free.

Java Simplified. Extensions and Useful Constructs for the Java Platform. Codeprimate Elements (a.k.a. cp-elements) is a Java library and micro-framework used to simplify the development of software applications written in Java. Elements packages several APIs into one library in order to address various application concerns and aspects of software design and development collectively and conveniently. Elements is a highly simple, yet robust and proven library built on solid OO principles, software design patterns and best practices to effectively solve common and reoccurring problems in software development. Write better Java!

Java Simplified. Extensions and Useful Constructs for the Java Platform. Codeprimate Elements (a.k.a. cp-elements) is a Java library and micro-framework used to simplify the development of software applications written in Java. Elements packages several APIs into one library in order to address various application concerns and aspects of software design and development collectively and conveniently. Elements is a highly simple, yet robust and proven library built on solid OO principles, software design patterns and best practices to effectively solve common and reoccurring problems in software development.

JSci is a set of open source Java packages. The aim is to encapsulate scientific methods/principles in the most natural way possible. As such they should greatly aid the development of scientific based software. It offers: abstract math interfaces, linear algebra (support for various matrix and vector types), statistics (including probability distributions), wavelets, newtonian mechanics, chart/graph components (AWT and Swing), MathML DOM implementation, ... Note: some packages, like javax.comm, for the astro and instruments package aren't listed as dependencies (not available).

Performs one-class classification on a dataset. Classifier reduces the class being classified to just a single class, and learns the datawithout using any information from other classes. The testing stage will classify as 'target'or 'outlier' - so in order to calculate the outlier pass rate the dataset must contain informationfrom more than one class. Also, the output varies depending on whether the label 'outlier' exists in the instances usedto build the classifier. If so, then 'outlier' will be predicted, if not, then the label willbe considered missing when the prediction does not favour the target class. The 'outlier' classwill not be used to build the model if there are instances of this class in the dataset. It cansimply be used as a flag, you do not need to relabel any classes. For more information, see: Kathryn Hempstalk, Eibe Frank, Ian H. Witten: One-Class Classification by Combining Density and Class Probability Estimation. In: Proceedings of the 12th European Conference on Principles and Practice of Knowledge Discovery in Databases and 19th European Conference on Machine Learning, ECMLPKDD2008, Berlin, 505--519, 2008.