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About: TurboParser is a free multilingual dependency parser based on linear programming developed by André Martins. It is based on joint work with Noah Smith, Mário Figueiredo, Eric Xing, Pedro Aguiar. Changes:This version introduces a number of new features:
Note: The runtimes above are approximate, and based on experiments with a desktop machine with a Intel Core i7 CPU 3.4 GHz and 8GB RAM. To run this software, you need a standard C++ compiler. This software has the following external dependencies: AD3, a library for approximate MAP inference; Eigen, a template library for linear algebra; google-glog, a library for logging; gflags, a library for commandline flag processing. All these libraries are free software and are provided as tarballs in this package. This software has been tested on Linux, but it should run in other platforms with minor adaptations.
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About: Learning string edit distance / similarity from data Changes:Added datasets used in the experiments of the paper
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About: The goal of this project is to provide code for reading and writing machine learning data sets for as many programming languages as possible. Changes:Forgot to include the Java sources.
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About: Generalized Ridge Regression (with special advantage for p >> n cases) Changes:Fetched by r-cran-robot on 2018-05-01 00:00:05.929954
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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: Genetic Algorithm for Curve Fitting Changes:Fetched by r-cran-robot on 2012-10-01 00:00:04.684941
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About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface. Changes:improved testing, improved documentation, windows compatibility, more algorithms
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About: This software is aimed at performing supervised/unsupervised learning on graph data, where each graph is represented as binary indicators of subgraph features. Changes:Initial Announcement on mloss.org.
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About: Investigation of dependencies between multiple data sources allows the discovery of regularities and interactions that are not seen in individual data sets. The demand for such methods is increasing with the availability and size of co-occurring observations in computational biology, open data initiatives, and in other domains. We provide practical, open access implementations of general-purpose algorithms that help to realize the full potential of these information sources. Changes:Three independent modules (drCCA, pint, MultiWayCCA) have been added.
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About: C-MixSim is an open source package written in C for simulating finite mixture models with Gaussian components. With a vast number of clustering algorithms, evaluating performance is important. C-MixSim provides an easy and convenient way of generating datasets from Gaussian mixture models with different levels of clustering complexity. C-MixSim is released under the GNU GPL license. Changes:Initial Announcement on mloss.org.
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About: A desktop planetarium and sky map program which shows the sky from anywhere on Earth at any time. Changes:Removed erroneous topocentric code. Increased maximum zoom for detail on planets.
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About: The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be [...] Changes:Initial Announcement on mloss.org.
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About: Regularization paths for SCAD- and MCP-penalized regression models Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.449164
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About: Model Monitor is a Java toolkit for the systematic evaluation of classifiers under changes in distribution. It provides methods for detecting distribution shifts in data, comparing the performance [...] Changes:Improved AUROC calculation. Several minor bug fixes.
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About: JNCC2 is the open-source implementation of the Naive Credal Classifier2 (NCC2), i.e., an extension of Naive Bayes towards imprecise probabilities, designed to deliver robust classifications even on [...] Changes:Initial Announcement on mloss.org.
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About: SVQP1 and SVQP2 are QP solvers for training SVM. Changes:Initial Announcement on mloss.org.
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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: This package contains functions to estimate linear and nonlinear regression methods with Penalized Partial Least Squares. Changes:
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About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting). Changes:
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About: SeqAn is an open source C++ library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data. Changes:
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