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zlib is designed to be a free, general-purpose, legally unencumbered -- that is, not covered by any patents -- lossless data-compression library for use on virtually any computer hardware and operating system. The zlib data format is itself portable across platforms. Unlike the LZW compression method used in Unix compress(1) and in the GIF image format, the compression method currently used in zlib essentially never expands the data. (LZW can double or triple the file size in extreme cases.) zlib's memory footprint is also independent of the input data and can be reduced, if necessary, at some cost in compression.

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.

The biblio transformation engine is a java framework developed by the Hellenic National Documentation Centre (EKT, www.ekt.gr) and consists of programmatic APIs for filtering and modifying records that are retrieved from various types of data sources (eg. databases, files, legacy data sources) as well as for outputing them in appropriate standards formats (eg. database files, txt, xml, Excel). The framework includes independent abstract modules that are executed seperately, offering in many cases alternative choices to the user depending of the input data set, the transformation workflow that needs to be executed and the output format that needs to be generated.

This package contains a classifier that can be used to train a two-class kernel logistic regression model with the kernel functions that are available in WEKA. It optimises the negative log-likelihood with a quadratic penalty. Both, BFGS and conjugate gradient descent, are available as optimisation methods, but the former is normally faster. It is possible to use multiple threads, but the speed-up is generally very marginal when used with BFGS optimisation. With conjugate gradient descent optimisation, greater speed-ups can be achieved when using multiple threads. With the default kernel, the dot product kernel, this method produces results that are close to identical to those obtained using standard logistic regression in WEKA, provided a sufficiently large value for the parameter determining the size of the quadratic penalty is used in both cases.

The biblio transformation engine is a java framework developed by the Hellenic National Documentation Centre (EKT, www.ekt.gr) and consists of programmatic APIs for filtering and modifying records that are retrieved from various types of data sources (eg. databases, files, legacy data sources) as well as for outputing them in appropriate standards formats (eg. database files, txt, xml, Excel). The framework includes independent abstract modules that are executed seperately, offering in many cases alternative choices to the user depending of the input data set, the transformation workflow that needs to be executed and the output format that needs to be generated.

This component may be plugged into standard compile plugin of maven to compile JavaFX ( http://javafx.com/) sources. The component assumes that JavaFX SDK 1.2+ is installed on the machine were built process is run. Environment variable JFX_HOME should point to JavaFX installation directory (typically /usr/share/javafx-sdk1.2 for Linux machines). Version 0.3 is current one and is stable. Version 0.2 has deffect and compiles only basic code samples in all other cases it simply fail.

How many classes does it take to make a cache? 60? 80? You might think so if you look at the other caches on the market. Ashkay is a streamlined, simple cache that in many ways is more powerful than the other mainstream caches. Ashkay is a strategy based caching tool. In most cases, you might be using a configuration file to tell the cache what rules it should obey. Or, you might just be setting properties on the cache. I have never liked this model as it limits me, the user of the cache to strategies the developer decided were important. Instead, Ashkay lets you choose the strategy(ies) to use when caching certain objects. Of course, a few of the most handy strategies are pre-packaged, but implementing a new one is a simple as can be. Ashkay is a fork of <a href="http://xot.sf.net">xot</a> caching code. Made more sense on its own.

Stepping is a framework designed to ease the implementation of data processing solutions. In use cases where we need to implement data or data-streaming algorithms or any other processing on data, we need to first handle many different infrastructure issues. For example, we need to decide how to split the data processing logic into different steps, think about our threading policy, how to handle communication between the different steps, error handling etc. One of the most important subjects is the Threading Policy of our solution. For example, we need to think how many threads to open, have the option to distribute the processing of data to multiple 'executors' in parallel, have a thread-safe communication layer between the threads etc. On top of that we also care a lot about the performance of our solution, we want to make sure that the latency added by these infrastructures is minimal as possible. Stepping aims to handle many of these aspects so developers can spend their time on the business logic instead of solving these infrastructure and data flow issues issues over and over again.

Generate feature file and cucumber report and execute and generate for VIRTUALAN or POSTMAN collection and used for API contract testing capability. - Used for API testing. - Used for Contract testing. - Used for Production Checkout. - Used for Agile sprint end regression testing.

GroupDocs.Editor for Java is a powerful document editing API using HTML. API can be used with any external, opensource or paid HTML editor. Editor API will process to load documents, convert it to HTML, provide HTML to external UI and then save HTML to original document after manipulation. It can also be used to generate different PDF files, Microsoft Word (DOC, DOCX), Excel spreadsheets (XLS, XSLSX), PowerPoint presentations (PPT, PPTX) and TXT documents. Manipulate Using HTML: Load Document Edit content using HTML Edit styles Perform Editor operations Convert back to supported file Document Editor is a computer program for editing HTML, the markup of a webpage. Although the HTML markup of a web page can be written with any text editor, specialized HTML editors can offer convenience and added functionality. For example, many HTML editors handle not only HTML, but also related technologies such as CSS, XML and JavaScript or ECMAScript. In some cases they also manage communication with remote web servers via FTP and WebDAV, and version control systems such as Subversion or Git. Many word processing, graphic design and page layout programs that are not dedicated to web design, such as Microsoft Word or Quark XPress, also have the ability to function as HTML editors.