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About: Python module for machine learning multivariate time series Changes:Initial Announcement on mloss.org.
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About: Baycomp is a library for Bayesian comparison of classifiers, as a better alternative for null-hypothesis significance testing. Changes:Initial Announcement on mloss.org.
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About: Somoclu is a massively parallel implementation of self-organizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Apart from a command line interface, Python, Julia, R, and MATLAB are supported. 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: Inference algorithms for models based on Luce's choice axiom. Changes:Initial Announcement on mloss.org.
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About: Behavior Optimization and Learning for Robots Changes:https://github.com/rock-learning/bolero/releases/tag/v1.0.0
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About: DataDeps is a package for simplifying the management of data in your julia application. In particular it is designed to make getting static data from some server into the local machine, and making programs know where that data is trivial. Changes:Initial Announcement on mloss.org.
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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: This database include 164 satellite iamges of different airports from google-earth, the first 110 images are used as training images, include 2337 aircrafts, the remained 54 images are used as test images, include 2206 aircrafts, each aircraft are labeled by two points and one number, indicating the positions of head and tail,and which point is the head. The labeled informations are recorded in two files: train.txt and test.txt, matlab is recommanded to be used for reading these data by import data tool. Changes:Initial Announcement on mloss.org.
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About: ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models. ruptures focuses on ease of use by providing a well-documented and consistent interface. In addition, thanks to its modular structure, different algorithms and models can be connected and extended within this package. Changes:Initial Announcement on mloss.org.
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About: The scancity of open database of small targets in remotesensing field has hindered the research in a lot. This open database includes 111 satellite images from google earth, 80 images are used as training set, contains 7862 vehicles. The other 31 images sre used as test set, contains 1635 vehicles. The positions of each vehicle are labeled by two points, which are recorded in "train.txt" and "test.txt" respectively. The label information is easily to be read by matlab tool. So such an open database is very useful for researchers in object detection fields. Changes:Initial Announcement on mloss.org.
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About: Classification and Regression Training Changes:Fetched by r-cran-robot on 2018-01-01 00:00:05.042473
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About: pycobra is a python library for ensemble learning, which serves as a toolkit for regression, classification, and visualisation. It is scikit-learn compatible and fits into the existing scikit-learn ecosystem. Changes:pycobra is further pep8 compliant, has improved tests and more plotting options.
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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...] Changes:This release include a lot of bug fixes and improvements. Some of these are detailed at http://jira.pentaho.com/projects/DATAMINING/issues/DATAMINING-771 As usual, for a complete list of changes refer to the changelogs.
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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: Operator Discretization Library (ODL) is a Python library that enables research in inverse problems on realistic or real data. Changes:Initial Announcement on mloss.org.
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About: A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation Changes:Release 0.7.0
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