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MOA is an open-source framework software that allows to build and run experiments of machine learning or data mining on evolving data streams. It includes a set of learners and stream generators that can be used from the graphical user interface (GUI), the command-line, and the Java API.
MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, cluster analysis, information extraction, topic modeling and other machine learning applications to text.
Test automation, mostly using unit testing, is a key feature of extreme programming and agile software development, where it is known as test-driven development (TDD) or test-first development. Unit tests can be written to define the functionality before the code is written.
It became well known in the ML competition circles after its use in the winning solution of the Higgs Machine Learning Challenge. Soon after, the Python and R packages were built, and XGBoost now has package implementations for Java, Scala, Julia, Perl, and other languages.
Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination of automation and ML. [1] AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment.
Selenium is an open-source automation framework for web applications, enabling testers and developers to automate browser interactions and perform functional testing. With versatile tools like WebDriver, Selenium supports various programming languages and facilitates cross-browser testing, making it a go-to choice for efficient and scalable web ...
Eclipse Deeplearning4j is a programming library written in Java for the Java virtual machine (JVM). [ 2 ] [ 3 ] It is a framework with wide support for deep learning algorithms. [ 4 ] Deeplearning4j includes implementations of the restricted Boltzmann machine , deep belief net , deep autoencoder, stacked denoising autoencoder and recursive ...
A long-polling Comet transport can be created by dynamically creating script elements, and setting their source to the location of the Comet server, which then sends back JavaScript (or JSONP) with some event as its payload. Each time the script request is completed, the browser opens a new one, just as in the XHR long polling case.