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Logo FsAlg 0.5.4

by gbaydin - April 25, 2015, 02:11:03 CET [ Project Homepage BibTeX Download ] 118 views, 16 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 ] 3143 views, 533 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 ] 10733 views, 2236 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 ] 226 views, 38 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 ] 1524 views, 276 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 ] 53579 views, 11386 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 ] 18665 views, 3035 downloads, 2 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.

Logo java machine learning platform 1.0

by openpr_nlpr - April 2, 2015, 09:02:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 451 views, 65 downloads, 2 subscriptions

About: Jmlp is a java platform for both of the machine learning experiments and application. I have tested it on the window platform. But it should be applicable in the linux platform due to the cross-platform of Java language. It contains the classical classification algorithm (Discrete AdaBoost.MH, Real AdaBoost.MH, SVM, KNN, MCE,MLP,NB) and feature reduction(KPCA,PCA,Whiten) etc.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-CoxBoost 1.4

by r-cran-robot - April 1, 2015, 00:00:04 CET [ Project Homepage BibTeX Download ] 19346 views, 3892 downloads, 3 subscriptions

About: Cox models by likelihood based boosting for a single survival endpoint or competing risks

Changes:

Fetched by r-cran-robot on 2015-04-01 00:00:04.730761


Logo r-cran-Boruta 4.0.0

by r-cran-robot - April 1, 2015, 00:00:04 CET [ Project Homepage BibTeX Download ] 9616 views, 2059 downloads, 2 subscriptions

About: Wrapper Algorithm for All-Relevant Feature Selection

Changes:

Fetched by r-cran-robot on 2015-04-01 00:00:04.111766


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