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Logo MDLText 1

by renatoms88 - March 3, 2016, 19:31:25 CET [ BibTeX Download ] 362 views, 126 downloads, 2 subscriptions

About: testing mloss.org

Changes:

Initial Announcement on mloss.org.


Logo JMLR MLPACK 2.0.1

by rcurtin - March 3, 2016, 18:52:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 57128 views, 10578 downloads, 6 subscriptions

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About: A scalable, fast C++ machine learning library, with emphasis on usability.

Changes:
  • Fix CMake to properly detect when MKL is being used with Armadillo.
  • Minor parameter handling fixes to mlpack_logistic_regression.
  • Properly install arma_config.hpp.
  • Memory handling fixes for Hoeffding tree code.
  • Add functions that allow changing training-time parameters to HoeffdingTree class.
  • Fix infinite loop in sparse coding test.
  • Documentation spelling fixes.
  • Properly handle covariances for Gaussians with large condition number, preventing GMMs from filling with NaNs during training (and also HMMs that use GMMs).
  • CMake fixes for finding LAPACK and BLAS as Armadillo dependencies when ATLAS is used.
  • CMake fix for projects using mlpack's CMake configuration from elsewhere.

Logo Local high order regularization 1.0

by kkim - March 2, 2016, 13:46:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 551 views, 116 downloads, 2 subscriptions

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About: Local high-order regularization for semi-supervised learning

Changes:

Initial Announcement on mloss.org.


Logo r-cran-BayesTree 0.3-1.3

by r-cran-robot - February 21, 2016, 00:00:00 CET [ Project Homepage BibTeX Download ] 8021 views, 1759 downloads, 1 subscription

About: Bayesian Additive Regression Trees

Changes:

Fetched by r-cran-robot on 2016-05-01 00:00:04.349689


Logo libcluster 2.3

by dsteinberg - February 27, 2016, 00:36:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3509 views, 733 downloads, 3 subscriptions

About: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.

Changes:

New maximum cluster argument for all algorithms. Also no more matlab interface since it seemed no one was using it, and I cannot support it any longer.


Logo APCluster 1.4.3

by UBod - February 25, 2016, 16:22:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30784 views, 5384 downloads, 3 subscriptions

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About: The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The package further provides leveraged affinity propagation, exemplar-based agglomerative clustering, and various tools for visual analysis of clustering results.

Changes:
  • added optional color legend to heatmap plotting; in line with this change, some minor changes to the interface of the heatmap() function
  • corresponding updates of help pages and vignette

Logo Somoclu 1.6.1

by peterwittek - February 22, 2016, 10:42:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14439 views, 2837 downloads, 3 subscriptions

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, R, and MATLAB are supported.

Changes:
  • New: Option for PCA initialization is added to the Python interface.
  • New: Clustering of the codebook with arbitrary clustering algorithm in scikit-learn is now possible in the Python interface.

About: Collection of algorithms for Gaussian Processes. Regression, Classification, Multi task, Multi output, Hierarchical, Sparse

Changes:

Initial Announcement on mloss.org.


Logo JMLR Jstacs 2.2

by keili - February 17, 2016, 11:57:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21346 views, 5005 downloads, 3 subscriptions

About: A Java framework for statistical analysis and classification of biological sequences

Changes:

New classes and packages:

  • CorreationCoefficient: PerformanceMeasure
  • de.jstacs.clustering: package with classes for hierarchical clustering
  • DeBruijnGraphSequenceGenerator and DeBruijnSequenceGenerator for generating De Buijn sequences
  • CyclicSequenceAdaptor for representing cyclic sequences
  • PlotGeneratorResult for representing results that plot images to a Graphics2D object
  • TextResult for results that may be stored as text files
  • package de.jstacs.results.savers for generic classes that store results to disk
  • LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder for sparse local inhomogeneous mixture (Slim) models
  • PFMWrapperTrainSM for representing position frequency matrices and position weight matrices from databases
  • package de.jstacs.tools with classes for generic Jstacs tools that may be used in different user interfaces (command line, Galaxy, JavaFX)
  • Compression for ZIP compression of Strings
  • package de.jstacs.utils.graphics with generic GraphicsAdaptor using Apache XML commons
  • projects: Dimont, GeMoMa, Slim, TALEN, motif comparison

New features and improvements:

  • Major restructuring of Alignment for better efficiency
  • Alignment Costs and StringAlignment now Storable
  • New constructor of DataSet allowing a specified percentage of sequences to mismatch the given alphabet
  • BioJavaAdapter ported to BioJava 1.9
  • XMLParser now also allows for storing Sequences
  • New method for parsing HMMer profile HMMs in HMMFactory
  • Several minor improvements and bugfixes in many classes
  • Improvements of documentation of several classes

Logo KeLP 2.0.2

by kelpadmin - February 17, 2016, 09:03:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7300 views, 1845 downloads, 3 subscriptions

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 bug fixes, this release includes:

  • the Nystrom method for linearizing instances and allowing a large scale kernel learning

  • New examples for the usage of the Smoothed Partial Tree Kernel and the Compositionally Smoothed Partial Tree Kernel.

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 2.0.2!


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