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About: The Easysvm package provides a set of tools based on the Shogun toolbox allowing to train and test SVMs in a simple way. Changes:Fixes for shogun 0.7.3.
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About: HDDM is a python toolbox for hierarchical Bayesian parameter estimation of the Drift Diffusion Model (via PyMC). Drift Diffusion Models are used widely in psychology and cognitive neuroscience to study decision making. Changes:
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About: Boosting algorithms for classification and regression, with many variations. Features include: Scalable and robust; Easily customizable loss functions; One-shot training for an entire regularization path; Continuous checkpointing; much more Changes:
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About: LibSGDQN proposes an implementation of SGD-QN, a carefully designed quasi-Newton stochastic gradient descent solver for linear SVMs. Changes:small bug fix (thx nicolas ;)
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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: Toeblitz is a MATLAB/Octave package for operations on positive definite Toeplitz matrices. It can solve Toeplitz systems Tx = b in O(n*log(n)) time and O(n) memory, compute matrix inverses T^(-1) (with free log determinant) in O(n^2) time and memory, compute log determinants (without inverses) in O(n^2) time and O(n) memory, and compute traces of products A*T for any matrix A, in minimal O(n^2) time and memory. Changes:Adding a write-up in written/toeblitz.pdf describing the package.
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About: The Rchemcpp package implements the marginalized graph kernel and extensions, Tanimoto kernels, graph kernels, pharmacophore and 3D kernels suggested for measuring the similarity of molecules. Changes:Moved from CRAN to Bioconductor. Improved handling of molecules, visualization and examples.
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About: Least Angle Regression, Lasso and Forward Stagewise Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.906244
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About: The library is focused on implementation of propagation based approximate inference methods. Also implemented are a clique tree based exact inference, Gibbs sampling, and the mean field algorithm. Changes:Initial Announcement on mloss.org.
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About: Aleph is both a multi-platform machine learning framework aimed at simplicity and performance, and a library of selected state-of-the-art algorithms. Changes:Initial Announcement on mloss.org.
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About: ALGLIB is an open source numerical analysis library distributed under GPL 2+. It implements both general numerical algorithms and machine learning algorithms. ALGLIB can be used from C#, C++, FreePascal, VBA and other languages. It is the only numerical analysis library which uses automatic translation to generate source code written in different programming languages with 100% identical functionality. Changes:
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About: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.305206
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About: Cluster quality Evaluation software. Implements cluster quality metrics based on ground truths such as Purity, Entropy, Negentropy, F1 and NMI. It includes a novel approach to correct for pathological or ineffective clusterings called 'Divergence from a Random Baseline'. Changes:Moved project to GitHub.
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About: Scalable learning of global, multi-task and local metrics from data Changes:Minor bug fix in multi-task objective computation (thanks to Junjie Hu).
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About: Probabilistic performance evaluation for multiclass classification using the posterior balanced accuracy Changes:Added bibtex information.
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About: A Matlab script for learning vector-valued functions and kernels on the output space. Changes:Added code for learning low-rank output kernels.
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About: Document/Text preprocessing for topic models: suite of Perl scripts for preprocessing text collections to create dictionaries and bag/list files for use by topic modelling software. Changes:Moved distribution and code across to GitHub. Changed "ldac" format to have 0 offset for word indices. Added "document frequency" (df) filtering on selection of tokens for linkTables. Playing with linkParse but its still unuseable generally.
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About: The SimpleSVM toolbox contains the svm solver of the same name. The current version includes C-SVM, HM-SVM and nu-SVM based on the regularization path. It will soon include OC-SVM, regularization [...] Changes:Initial Announcement on mloss.org.
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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: A native Python, scikit-compatible, implementation of a variety of multi-label classification algorithms. Changes:
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