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.

Initial Announcement on mloss.org.

About: EANT Without Structural Optimization is used to learn a policy in either complete or partially observable reinforcement learning domains of continuous state and action space.

Initial Announcement on mloss.org.

About: Incremental (Online) Nonparametric Classifier. You can classify both points (standard) or matrices (multivariate time series). Java and Matlab code already available.

version 2: parameterless system, constant model size, prediction confidence (for active learning).

NEW!! C++ version at: https://github.com/ilaria-gori/ABACOC

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.

• 5 more applications, i.e. DFI, MicroRazerS, PairAlign, SeqCons, TreeRecon
• stable release of RazerS supporting paired-end read mapping and configurable sensitivity
• new alignment algorithms, e.g. banded, configurable alignments (overlap, semi-global, ...)
• realignment algorithm
• NGS data structures and formats, e.g. SAM, Amos, ...
• new alphabets, e.g. Dna with base call qualities, profile characters
• auxiliary data structures and algorithms, e.g. double ended queue, command line parser
• positional scores
• CMake support

About: A chatterbot that learns natural languages learning from imitation.

Alpha 1 - Codename: Wendell Borton ("Bllluuhhhhh...!!")

Short term memory greatly improved.

About: This software implements the DeltaLDA model, which is a modification of the Latent Dirichlet Allocation (LDA) model. DeltaLDA can use multiple topic mixing weight priors to jointly model multiple [...]

-fixed some npy_intp[] memory leaks -fixed phi normalization bug

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.

This version introduces a number of new features:

• The parser does not depend anymore on CPLEX (or any other non-free LP solver). Instead, the decoder is now based on AD3, our free library for approximate MAP inference.

• The parser now outputs dependency labels along with the backbone structure.

• As a bonus, we now provide a trainable part-of-speech tagger, called TurboTagger, which can be used in standalone mode, or to provide part-of-speech tags as input for the parser. TurboTagger has state-of-the-art accuracy for English (97.3% on section 23 of the Penn Treebank) and is fast (~40,000 tokens per second).

• The parser is much faster than in previous versions. You may choose among a basic arc-factored parser (~4,300 tokens per second), a standard second-order model with consecutive sibling and grandparent features (the default; ~1,200 tokens per second), and a full model with head bigram and arbitrary sibling features (~900 tokens per second).

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.

About: CRFSuite is a speed-oriented implementation of Conditional Random Fields (CRFs). This software features: parameter estimation using SGD and L-BFGS, l1/l2 regularization, simple data I/O format, etc.

Initial Announcement on mloss.org.

About: Aika is an open source text mining engine. It can automatically extract and annotate semantic information in text. In case this information is ambiguous, Aika will generate several hypothetical interpretations about the meaning of this text and retrieve the most likely one.

Aika Version 0.17 2018-05-14

• Introduction of synapse relations. Previously the relation between synapses was implicitly modeled through word positions (RIDs). Now it is possible to explicitly model relations like: The end position of input activation 1 equals to the begin position of input activation 2. Two types of relations are currently supported, range relations and instance relations. Range relations compare the input activation range of a given synapse with that of the linked synapse. Instance relations also compare the input activations of two synapses, but instead of the ranges the dependency relations of these activations are compared.
• Removed the norm term from the interpretation objective function.
• Introduction of an optional distance function to synapses. It allows to model a weakening signal depending on the distance of the activation ranges.
• Example implementation of a context free grammar.
• Example implementation for co-reference resolution.
• Work on an syllable identification experiment based on the meta network implementation.

Aika Version 0.15 2018-03-16

• Simplified interpretation handling by removing the InterpretationNode class and moving the remaining logic to the Activation class.
• Moved the activation linking and activation selection code to separate classes.
• Ongoing work on the training algorithms.

About: BSVM solves support vector machines (SVM) for the solution of large classification and regression problems. It includes three methods

Initial Announcement on mloss.org.

About: dysii is a C++ library for distributed probabilistic inference and learning in large-scale dynamical systems. It provides methods such as the Kalman, unscented Kalman, and particle filters and [...]

Initial Announcement on mloss.org.

About: Java package implementing a kernel for (molecular) graphs based on iterative graph similarity and optimal assignments.

Initial Announcement on mloss.org.

About: Matlab implementation of variational gaussian approximate inference for Bayesian Generalized Linear Models.

Code restructure and bug fix.

About: Fitting user specified models with Group Lasso penalty

Fetched by r-cran-robot on 2013-04-01 00:00:05.428021

About: Local alignment kernels measure the similarity between two sequences by summing up scores obtained from local alignments with gaps of the sequences.

Initial Announcement on mloss.org.

About: Learning string edit distance / similarity from data

Added datasets used in the experiments of the paper

About: HLearn makes simple machine learning routines available in Haskell by expressing them according to their algebraic structure

Updated to version 1.0

About: Sequin is an open source sequence mining library written in C#.

Sequin v1.1.0.0 released

About: This package provides an implementation Schapire and Singer's AdaBoost.MH for multi-label classification. As a main feature, the package provides decision-tree weak learning, a generalization of [...]

Initial Announcement on mloss.org.

About: Alchemy is a software package providing a series of algorithms for statistical relational learning and probabilistic logic inference, based on the Markov logic representation. Alchemy allows you to [...]

Initial Announcement on mloss.org.