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Logo KeBABS 1.2.0

by UBod - April 17, 2015, 21:15:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2801 views, 466 downloads, 3 subscriptions

About: Kernel-Based Analysis of Biological Sequences

Changes:
  • inclusion of dense LIBSVM 3.20 for dense kernel matrix support to provide a reliable way for training with kernel matrices
  • new accessors folds and performance for CrossValidationResult
  • removed fold performance from show of CV result
  • adaptions for user defined sequence kernel with new export isUserDefined, example in inst/examples/UserDefinedKernel
  • correction of errors with position offset for position specific kernels
  • computation of AUC via trapezoidal rule
  • changes for auto mode in CV, grid search, model selection
  • check for non-negative mixing coefficients in spectrum and gappy pair kernel
  • build warnings on Windows removed
  • added definition of performance parameters for binary and multiclass classification to vignette
  • update of citation file and reference section in help pages

Logo Choquistic Utilitaristic Regression 1.00

by AliFall - April 17, 2015, 11:31:20 CET [ BibTeX BibTeX for corresponding Paper Download ] 115 views, 10 downloads, 1 subscription

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 ] 1200 views, 235 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 python weka wrapper 0.3.0

by fracpete - April 15, 2015, 12:37:22 CET [ Project Homepage BibTeX Download ] 10327 views, 2159 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 method "ndarray_to_instances" to "weka.converters" module for converting Numpy 2-dimensional array into "Instances" object
  • added method "plot_learning_curve" to "weka.plot.classifiers" module for creating learning curves for multiple classifiers for a specific metric
  • added plotting of experiments with "plot_experiment" methid in "weka.plot.experiments" module
  • "Instance.create_instance" method now takes list of tuples (index, internal float value) when generating sparse instances
  • added "weka.core.database" module for loading data from a database
  • added "make_copy" class method to "Clusterer" class
  • added "make_copy" class method to "Associator" class
  • added "make_copy" class method to "Filter" class
  • added "make_copy" class method to "DataGenerator" class
  • most classes (like Classifier and Filter) now have a default classname value in the constructor
  • added "TextDirectoryLoader" class to "weka.core.converters"
  • moved all methods from "weka.core.utils" to "weka.core.classes"
  • fixed "Attribute.index_of" method for determining label index
  • fixed "Attribute.add_string_value" method (used incorrect JNI parameter)
  • "create_instance" and "create_sparse_instance" methods of class "Instance" now ensure that list values are float
  • added "to_help" method to "OptionHandler" class which outputs a help string generated from the base class's "globalInfo" and "listOptions" methods
  • fixed "test_model" method of "Evaluation" class when supplying a "PredictionOutput" object (previously generated "No dataset structure provided!" exception)
  • added "batch_finished" method to "Filter" class for incremental filtering
  • added "line_plot" method to "weka.plot.dataset" module for plotting dataset using internal format (one line plot per instance)
  • added "is_serializable" property to "JavaObject" class
  • added "has_class" convenience property to "Instance" class
  • added "repr" method to "JavaObject" classes (simply calls "toString()" method)
  • added "Stemmer" class in module "weka.core.stemmers"
  • added "Stopwords" class in module "weka.core.stopwords"
  • added "Tokenizer" class in module "weka.core.tokenizers"
  • added "StringToWordVector" filter class in module "weka.filters"
  • added simple workflow engine (see documentation on Flow)

Logo Armadillo library 5.000

by cu24gjf - April 13, 2015, 05:05:36 CET [ Project Homepage BibTeX Download ] 53057 views, 11286 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 ] 18481 views, 2992 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 ] 322 views, 42 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 ] 19191 views, 3862 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 ] 9466 views, 2028 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


Logo Blocks 0.1

by bartvm - March 30, 2015, 22:25:02 CET [ Project Homepage BibTeX Download ] 337 views, 54 downloads, 2 subscriptions

About: A Theano framework for building and training neural networks

Changes:

Initial Announcement on mloss.org.


Showing Items 1-10 of 570 on page 1 of 57: 1 2 3 4 5 6 Next Last