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Logo KeLP 1.0.0

by kelpadmin - April 27, 2015, 16:44:36 CET [ Project Homepage BibTeX Download ] 65 views, 9 downloads, 1 subscription

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 classifiers without writing a single line of code.

Changes:

Initial Announcement on mloss.org.


Logo BLOG 0.9.1

by jxwuyi - April 27, 2015, 06:52:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 96 views, 5 downloads, 1 subscription

About: Bayesian Logic (BLOG) is a probabilistic modeling language. It is designed for representing relations and uncertainties among real world objects.

Changes:

Initial Announcement on mloss.org.


Logo DiffSharp 0.6.0

by gbaydin - April 27, 2015, 01:47:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 81 views, 9 downloads, 1 subscription

About: DiffSharp is an automatic differentiation (AD) library providing gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products. It allows exact and efficient calculation of derivatives, with support for nesting.

Changes:

Initial Announcement on mloss.org.


Logo FsAlg 0.5.4

by gbaydin - April 25, 2015, 02:11:03 CET [ Project Homepage BibTeX Download ] 165 views, 27 downloads, 1 subscription

About: FsAlg is a linear algebra library that supports generic types.

Changes:

Initial Announcement on mloss.org.


Logo KeBABS 1.2.1

by UBod - April 23, 2015, 13:55:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3210 views, 543 downloads, 3 subscriptions

About: Kernel-Based Analysis of Biological Sequences

Changes:
  • correction of error in model selection for processing via dense LIBSVM
  • remove problem in check for loading of SparseM

Logo python weka wrapper 0.3.1

by fracpete - April 23, 2015, 00:06:57 CET [ Project Homepage BibTeX Download ] 10830 views, 2245 downloads, 3 subscriptions

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:
  • added "get_tags" class method to "Tags" class for easier instantiation of Tag arrays
  • added "find" method to "Tags" class to locate "Tag" object that matches the string
  • fixed "getitem" and "setitem" methods of the "Tags" class
  • added "GridSearch" meta-classifier with convenience properties to module "weka.classifiers"
  • added "SetupGenerator" and various parameter classes to "weka.core.classes"
  • added "MultiSearch" meta-classifier with convenience properties to module "weka.classifiers"
  • added "quote"/"unquote" and "backquote"/"unbackquote" methods to "weka.core.classes" module
  • added "main" method to "weka.core.classes" for operations on options: join, split, code
  • added support for option handling to "weka.core.classes" module

Logo Choquistic Utilitaristic Regression 1.00

by AliFall - April 17, 2015, 11:31:20 CET [ BibTeX BibTeX for corresponding Paper Download ] 239 views, 42 downloads, 2 subscriptions

About: This Matlab package implements a method for learning a choquistic regression model (represented by a corresponding Moebius transform of the underlying fuzzy measure), using the maximum likelihood approach proposed in [2], eqquiped by sigmoid normalization, see [1].

Changes:

Initial Announcement on mloss.org.


Logo OpenNN 2.0

by Sergiointelnics - April 16, 2015, 18:38:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1549 views, 278 downloads, 3 subscriptions

About: OpenNN is an open source class library written in C++ which implements neural networks. The library has been designed to learn from both data sets and mathematical models.

Changes:

New utilities, correction of bugs, parallelization with OpenMP.


Logo Armadillo library 5.000

by cu24gjf - April 13, 2015, 05:05:36 CET [ Project Homepage BibTeX Download ] 53682 views, 11401 downloads, 4 subscriptions

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About: Armadillo is a template C++ linear algebra library aiming towards a good balance between speed and ease of use, with a function syntax similar to MATLAB. Matrix decompositions are provided through optional integration with LAPACK, or one of its high performance drop-in replacements (eg. Intel MKL, OpenBLAS).

Changes:
  • added spsolve() for solving sparse systems of linear equations
  • added svds() for singular value decomposition of sparse matrices
  • added nonzeros() for extracting non-zero values from matrices
  • added handling of diagonal views by sparse matrices
  • expanded repmat() to handle sparse matrices
  • expanded join_rows() and join_cols() to handle sparse matrices
  • sort_index() and stable_sort_index() have been placed in the delayed operations framework for increased efficiency
  • use of 64 bit integers is automatically enabled when using C++11
  • workaround for a bug in recent releases of Apple Xcode
  • workaround for a bug in LAPACK 3.5

Logo Cognitive Foundry 3.4.0

by Baz - April 3, 2015, 08:28:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18727 views, 3043 downloads, 3 subscriptions

About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications.

Changes:
  • General:
    • Now requires Java 1.7 or higher.
    • Improved compatibility with Java 1.8 functions by removing ClonableSerializable requirement from many function-style interfaces.
  • Common Core:
    • Improved iteration speed over sparse MTJ vectors.
    • Added utility methods for more stable log(1+x), exp(1-x), log(1 - exp(x)), and log(1 + exp(x)) to LogMath.
    • Added method for creating a partial permutations to Permutation.
    • Added methods for computing standard deviation to UnivariateStatisticsUtil.
    • Added increment, decrement, and list view methods to Vector and Matrix.
    • Added shorter versions of get and set for Vector and Matrix getElement and setElement.
    • Added aliases of dot for dotProduct in VectorSpace.
    • Added utility methods for divideByNorm2 to VectorUtil.
  • Learning:
    • Added a learner for a Factorization Machine using SGD.
    • Added a iterative reporter for validation set performance.
    • Added new methods to statistical distribution classes to allow for faster sampling without boxing, in batches, or without creating extra memory.
    • Made generics for performance evaluators more permissive.
    • ParameterGradientEvaluator changed to not require input, output, and gradient types to be the same. This allows more sane gradient definitions for scalar functions.
    • Added parameter to enforce a minimum size in a leaf node for decision tree learning. It is configured through the splitting function.
    • Added ability to filter which dimensions to use in the random subspace and variance tree node splitter.
    • Added ReLU, leaky ReLU, and soft plus activation functions for neural networks.
    • Added IntegerDistribution interface for distributions over natural numbers.
    • Added a method to get the mean of a numeric distribution without boxing.
    • Fixed an issue in DefaultDataDistribution that caused the total to be off when a value was set to less than or equal to 0.
    • Added property for rate to GammaDistribution.
    • Added method to get standard deviation from a UnivariateGaussian.
    • Added clone operations for decision tree classes.
    • Fixed issue TukeyKramerConfidence interval computation.
    • Fixed serialization issue with SMO output.

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