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About: A fast, flexible C++ machine learning library, with bindings to other languages. Changes:Released June 8th, 2018.
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About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. Changes:This release adds a bunch of new image processing routines as well as many minor usability improvements and bug fixes.
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About: Armadillo is a high quality C++ library for linear algebra & scientific computing, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products). Changes:
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About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlab-like development environment. Changes:
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About: A thin Python3 wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Changes:
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About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Changes:
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About: Kernel-based Learning Platform (KeLP) is Java framework that supports the implementation of kernel-based learning algorithms, as well as an agile definition of kernel functions over generic data representation, e.g. vectorial data or discrete structures. The framework has been designed to decouple kernel functions and learning algorithms, through the definition of specific interfaces. Once a new kernel function has been implemented, it can be automatically adopted in all the available kernel-machine algorithms. KeLP includes different Online and Batch Learning algorithms for Classification, Regression and Clustering, as well as several Kernel functions, ranging from vector-based to structural kernels. It allows to build complex kernel machine based systems, leveraging on JSON/XML interfaces to instantiate prediction models without writing a single line of code. Changes:In addition to minor improvements and bug fixes, this release includes:
Check out this new version from our repositories. API Javadoc is already available. Your suggestions will be very precious for us, so download and try KeLP 2.2.2!
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About: Armadillo/C++ implementation of the Indefinite Core Vector Machine Changes:Some tiny errors in the Nystroem demo scripts - should be ok now Initial Announcement on mloss.org.
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About: The Advanced Data mining And Machine learning System (ADAMS) is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes. Changes:Some highlights:
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About: This is a tool for retrieving nearest neighbors and clustering of large categorical data sets represented in transactional form. The clustering is achieved via a locality-sensitive hashing of categorical datasets for speed and scalability. Changes:Initial Announcement on mloss.org.
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About: Large scale, distributed graph processing made easy. Changes:Graph partitioning methods APSP approximation method Performance improvements License change Bug fixes
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About: DynaML is a Scala environment for conducting research and education in Machine Learning. DynaML comes packaged with a powerful library of classes implementing predictive models and a Scala REPL where one can not only build custom models but also play around with data work-flows. Changes:Initial Announcement on mloss.org.
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About: ADENINE (A Data ExploratioN pIpeliNE) is a machine learning framework for data exploration that encompasses state-of-the-art techniques for missing values imputing, data preprocessing, unsupervised feature learning and clustering tasks. Changes:
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About: NaN-toolbox is a statistics and machine learning toolbox for handling data with and without missing values. Changes:Changes in v.3.1.2 - improve configuration and build system - support of more platforms (including Octave 4.2.0) improved Changes in v.3.0.3 - improve compatibility for Octave on Windows Changes in v.3.0.1 - fix packaging for octave Changes in v.2.8.5 - bug fix: trimmean - compiler support for gcc-5 and clang - fix typos For details see the CHANGELOG at http://pub.ist.ac.at/~schloegl/matlab/NaN/CHANGELOG
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About: LogReg-Crowds is a collection of Julia implementations of various approaches for learning a logistic regression model multiple annotators and crowds, namely the works of Raykar et al. (2010), Rodrigues et al. (2013) and Dawid and Skene (1979). Changes:Initial Announcement on mloss.org. Added GitHub page.
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About: General purpose Java Machine Learning library for classification, regression, and clustering. Changes:See github release tab for change info
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About: DIANNE is a modular software framework for designing, training and evaluating artificial neural networks on heterogeneous, distributed infrastructure . It is built on top of OSGi and AIOLOS and can transparently deploy and redeploy (parts of) a neural network on multiple machines, as well as scale up training on a compute cluster. Changes:Initial Announcement on mloss.org.
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About: machine learning library in java for easy development of new kernels and kernel algorithms Changes:Version 3.0 /! Warning: this version is incompatible with previous code
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About: Analytic engine for real-time large-scale streams containing structured and unstructured data. Changes:Initial Announcement on mloss.org.
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About: Jatecs is an open source Java library focused on automatic text categorization. Changes:Initial Announcement on mloss.org.
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