Download JAR files tagged by useful with all dependencies

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.

mXparser is a super easy, rich, fast and highly flexible math expression parser library (parser and evaluator of mathematical expressions / formulas provided as plain text / string). Software delivers easy to use API for JAVA, Android and C# .NET/MONO (Common Language Specification compliant: F#, Visual Basic, C++/CLI). *** If you find the software useful donation or purchase is something you might consider: https://mathparser.org/donate/ *** Online store: https://payhip.com/INFIMA *** Scalar Scientific Calculator, Charts and Scripts, Scalar Lite: https://play.google.com/store/apps/details?id=org.mathparser.scalar.lite *** Scalar Pro: https://play.google.com/store/apps/details?id=org.mathparser.scalar.pro *** ScalarMath.org: https://scalarmath.org/ *** MathSpace.pl: https://mathspace.pl/ ***

Easy to install library for adding dynamic display, control and configuration of java.util.logging to any swing based application. Useful for debugging apps in production situations; can interactively configure logging while an application is running including adding a handler to save logging output to a file. Changes made to an application's default/startup logging can be saved and automatically applied at startup. LogMan "single" library package for use in swing apps. The jar can be executed, "java -jar xxx", for a demo of the library. See com.raelity.logman.demo.Main for an example of adding the library to a swing app.

This project has a lot of business classes to work with genes and related named entities. Genes are part of a GeneDocument and may have gold IDs as well as mapped/predicted IDs. Another large part are species because most (all?) gene ID databases are species specific. So there are also classes or members to represent species mentions and the assignment of species IDs (taxonomy IDs) to genes. There is little to no business logic herein. This project is only useful as building block in other projects dealing with species assignment, gene ID mapping or similar efforts.

A very simple, no-dependencies drawing API providing some primitive operations including lines, rectangles, circles, ellipses, arcs. It doesn't actually draw TO anything, you must provide your own implementation of Backing to actually paint the pixels. This project is intended for use with Snake, my project for Razer devices on Linux, but is made available in case others may find it useful. It doesn't have anything fancy like anti-alias, transformations or even line widths, contributions welcome though!

Burningwave core is an advanced, free and open source Java library that contains THE MOST POWERFUL CLASSPATH SCANNER for criteria based classes search. It’s possible to search classes by every criteria that your immagination can made by using lambda expressions. Burningwave core scan engine is highly optimized using direct allocated ByteBuffers to avoid heap saturation; searches are executed in multithreading context and are not affected by “the issue of the same class loaded by different classloaders” (normally if you try to execute "isAssignableFrom" method on a same class loaded from different classloader it return false). This library is useful also for creating classes during runtime, facilitate the use of reflection and much more...

Package containing a class that rescales the attributes in a classification problem based on their discriminative power. This is useful as a pre-processing step for learning algorithms such as the k-nearest-neighbour method, to replace simple normalization. Each attribute is rescaled by multiplying it with a learned weight. All attributes excluding the class are assumed to be numeric and missing values are not permitted. To achieve the rescaling, this package also contains an implementation of non-negative logistic regression, which produces a logistic regression model with non-negative weights .

A simple meta-classifier that uses a clusterer for classification. For cluster algorithms that use a fixed number of clusterers, like SimpleKMeans, the user has to make sure that the number of clusters to generate are the same as the number of class labels in the dataset in order to obtain a useful model. Note: at prediction time, a missing value is returned if no cluster is found for the instance. The code is based on the 'clusters to classes' functionality of the weka.clusterers.ClusterEvaluation class by Mark Hall.

The crypto4j library provides a simple and pluggable crypto abstraction library for Java, including both cryptographic primitives and the artifacts defined in the JOSE standard. This library separates the cryptographic primitives from the JOSE artifacts. The library uses the algorithms available through JCA (JCE). The implementations of the cryptographic primitives provided in this library rely on the standard JCA implementation, and can be configured and extended through the JCA mechanisms. The JOSE portion of the library allows custom extensions by either replacing the provided JOSE artifact implementations with custom implementations, or by adding new JOSE artifacts, for instance in form of additional algorithms, which is particularly useful in case that the JOSE standard is updated or in case custom extensions to the JOSE standard should be implemented. The implementations available in this library generally come in two variants: a standard implementation of the primitives and advanced algorithms, and a high-performance implementation that takes advantage of implementation patterns that do not compromise cryprographic security, but speed up the overall processing time.

We propose two efficient algorithms for exploring topic diversity in large document corpora such as user generated content on the social web, bibliographic data, or other web repositories. Analyzing diversity is useful for obtaining insights into knowledge evolution, trends, periodicities, and topic heterogeneity of such collections. Calculating diversity statistics requires averaging over the similarity of all object pairs, which, for large corpora, is prohibitive from a computational point of view. Our proposed algorithms overcome the quadratic complexity of the average pair-wise similarity computation, and allow for constant time (depending on dataset properties) or linear time approximation with probabilistic guarantees.