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About: LIBOL is an open-source library that consists of a family of state-of-the-art online learning algorithms for machine learning and data mining research. Changes:Initial Announcement on mloss.org.
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About: This package contains a python and a matlab implementation of the most widely used algorithms for multi-armed bandit problems. The purpose of this package is to provide simple environments for comparison and numerical evaluation of policies. Changes:Initial Announcement on mloss.org.
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About: Locally Weighted Projection Regression (LWPR) is a recent algorithm that achieves nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its [...] Changes:Version 1.2.4
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About: OpenViBE is an opensource platform that enables to design, test and use Brain-Computer Interfaces (BCI). Broadly speaking, OpenViBE can be used in many real-time Neuroscience applications [...] Changes:New release 0.8.0.
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About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license. Changes:Initial Announcement on mloss.org.
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About: A fast implementation of several stochastic gradient descent learners for classification, ranking, and ROC area optimization, suitable for large, sparse data sets. Includes Pegasos SVM, SGD-SVM, Passive-Aggressive Perceptron, Perceptron with Margins, Logistic Regression, and ROMMA. Commandline utility and API libraries are provided. Changes:Initial Announcement on mloss.org.
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About: Elefant is an open source software platform for the Machine Learning community licensed under the Mozilla Public License (MPL) and developed using Python, C, and C++. We aim to make it the platform [...] Changes:This release contains the Stream module as a first step in the direction of providing C++ library support. Stream aims to be a software framework for the implementation of large scale online learning algorithms. Large scale, in this context, should be understood as something that does not fit in the memory of a standard desktop computer. Added Bundle Methods for Regularized Risk Minimization (BMRM) allowing to choose from a list of loss functions and solvers (linear and quadratic). Added the following loss classes: BinaryClassificationLoss, HingeLoss, SquaredHingeLoss, ExponentialLoss, LogisticLoss, NoveltyLoss, LeastMeanSquareLoss, LeastAbsoluteDeviationLoss, QuantileRegressionLoss, EpsilonInsensitiveLoss, HuberRobustLoss, PoissonRegressionLoss, MultiClassLoss, WinnerTakesAllMultiClassLoss, ScaledSoftMarginMultiClassLoss, SoftmaxMultiClassLoss, MultivariateRegressionLoss Graphical User Interface provides now extensive documentation for each component explaining state variables and port descriptions. Changed saving and loading of experiments to XML (thereby avoiding storage of large input data structures). Unified automatic input checking via new static typing extending Python properties. Full support for recursive composition of larger components containing arbitrary statically typed state variables.
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About: This package implements the “Online Random Forests” (ORF) algorithm of Saffari et al., ICCV-OLCV 2009. This algorithm extends the offline Random Forests (RF) to learn from online training data samples. ORF is a multi-class classifier which is able to learn the classifier without 1-vs-all or 1-vs-1 binary decompositions. Changes:Initial Announcement on mloss.org.
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About: Reference implementation of the LASVM online and active SVM algorithms as described in the JMLR paper. The interesting bit is a small C library that implements the LASVM process and reprocess [...] Changes:Minor bug fix
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About: Debellor is a scalable and extensible platform which provides common architecture for data mining and machine learning algorithms of various types. Changes:
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About: OLaRankGreedy is an online solver of the dual formulation of support vector machines for sequence labeling using greedy inference. Changes:Initial Announcement on mloss.org.
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About: OLaRank is an online solver of the dual formulation of support vector machines for sequence labeling using viterbi decoding. Changes:Initial Announcement on mloss.org.
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About: Piqle (Platform for Implementing Q-Learning Experiments) is a Java framework for fast design, prototyping and test of reinforcement learning experiments (RL). By clearly separating algorithms and problems, it allows users to focus on either part of the RL paradigm:designing new algorithms or implementing new problems. Piqle implements many classical RL algorithms, making their parameters easily tunable. At this time, 13 problems are implemented, several with one or more variants. The user's manual explains in detail how to code a new problem. Written in Java, Piqle is as platform-independent as Java itself. Its components can easily be embedded as part of complex implementations, like robotics or decision making. Changes:Initial Announcement on mloss.org.
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About: OLL is a library supporting several for online-learning algorithms, which provides C++ library, and stand-alone programs for learning, predicting. OLL is specialized for large-scale, but sparse, [...] Changes:Initial Announcement on mloss.org.
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About: Ohmm is a library for learning hidden Markov models by using Online EM algorithm. This library is specialized for large scale data; e.g. 1 million words. The output includes parameters, and estimation results. Changes:Initial Announcement on mloss.org.
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About: Nieme is a C++ machine learning library for large-scale classification, regression and ranking. It provides a simple interface available in C++, Python and Java and a user interface for visualization. Changes:Released Nieme 1.0
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About: This software package includes the ART algorithms for unsupervised learning only. It is a family of four programs based on different ART algorithms (ART 1, ART 2A, ART 2A-C and ART Distance). All of [...] Changes:Initial Announcement on mloss.org.
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About: LaRank is an online solver for multiclass Support Vector Machines. Changes:Initial Announcement on mloss.org.
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About: This is a large scale online learning implementation with several useful features. See the webpage for more details. Changes:Initial Announcement on mloss.org.
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