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Logo r-cran-biglasso 1.3-3

by r-cran-robot - January 24, 2017, 00:00:00 CET [ Project Homepage BibTeX Download ] 432 views, 58 downloads, 2 subscriptions

About: Extending Lasso Model Fitting to Big Data

Changes:

Initial Announcement on mloss.org by r-cran-robot


Logo NaN toolbox 3.1.2

by schloegl - January 22, 2017, 12:24:59 CET [ Project Homepage BibTeX Download ] 55986 views, 11316 downloads, 3 subscriptions

About: NaN-toolbox is a statistics and machine learning toolbox for handling data with and without missing values.

Changes:

Changes in v.3.1.2 - improve configuration and build system - support of more platforms (including Octave 4.2.0) improved

Changes in v.3.0.3 - improve compatibility for Octave on Windows

Changes in v.3.0.1 - fix packaging for octave

Changes in v.2.8.5 - bug fix: trimmean - compiler support for gcc-5 and clang - fix typos

For details see the CHANGELOG at http://pub.ist.ac.at/~schloegl/matlab/NaN/CHANGELOG


Logo MLweb 0.1.5

by lauerfab - January 17, 2017, 15:47:41 CET [ Project Homepage BibTeX Download ] 7401 views, 1670 downloads, 3 subscriptions

About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlab-like development environment.

Changes:
  • Optimize use of kernel cache in MSVM.tune()
  • A few other speed-ups (for spectral clustering, eigs, ...)
  • Add colormap() to Lalolab for colormap plots
  • Changes in some examples
  • Minor bug fixes (including plots in IE)

Logo LogRegCrowds, Logistic Regression from Crowds 1.0

by fmpr - January 16, 2017, 18:10:57 CET [ Project Homepage BibTeX Download ] 2926 views, 776 downloads, 3 subscriptions

About: LogReg-Crowds is a collection of Julia implementations of various approaches for learning a logistic regression model multiple annotators and crowds, namely the works of Raykar et al. (2010), Rodrigues et al. (2013) and Dawid and Skene (1979).

Changes:

Initial Announcement on mloss.org. Added GitHub page.


Logo Multi Annotator Supervised LDA for regression 1.0

by fmpr - January 16, 2017, 18:10:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 649 views, 79 downloads, 3 subscriptions

About: MA-sLDAr is a C++ implementation of the supervised topic models with response variables provided by multiple annotators with different levels of expertise.

Changes:

Initial Announcement on mloss.org.


Logo Multi Annotator Supervised LDA for classification 1.0

by fmpr - January 16, 2017, 18:01:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 611 views, 69 downloads, 3 subscriptions

About: MA-sLDAc is a C++ implementation of the supervised topic models with labels provided by multiple annotators with different levels of expertise.

Changes:

Initial Announcement on mloss.org.


Logo Java Statistical Analysis Tool 0.0.7

by EdwardRaff - January 15, 2017, 22:21:50 CET [ Project Homepage BibTeX Download ] 2224 views, 550 downloads, 2 subscriptions

About: General purpose Java Machine Learning library for classification, regression, and clustering.

Changes:

See github release tab for change info


Logo FEAST 2.0.0

by apocock - January 8, 2017, 00:49:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 42062 views, 7490 downloads, 3 subscriptions

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About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:

Major refactoring of FEAST to improve speed and portability.

  • FEAST now clones the input data if it's floating point and discretises it to unsigned ints once in a single pass. This improves the speed by about 30%.
  • FEAST now has unsigned int entry points which avoid this discretisation and are much faster if the data is already categorical.
  • Added weighted feature selection algorithms to FEAST which can be used for cost-sensitive feature selection.
  • Added a Java API using JNI.
  • FEAST now returns the internal score for each feature according to the criterion. Available in all three APIs.
  • Rearranged the repository to make it easier to work with. Header files are now in `include`, source in `src`, the MATLAB API is in `matlab/` and the Java API is in `java/`.
  • FEAST now compiles cleanly using `-std=c89 -Wall -Werror`.

Logo MIToolbox 3.0.0

by apocock - January 8, 2017, 00:43:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 31114 views, 5230 downloads, 3 subscriptions

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features.

Changes:

Major refactor of code and reorganised the repository so it's a little more sensible.

  • Refactored all C functions to expose a version which takes unsigned integer inputs.
  • Rearranged the repository to separate out headers from source, and MATLAB code from C library code.

Minor changes:

  • General code cleanup to reduce duplicated code.
  • Adding an COMPILE_R flag to go with the COMPILE_C flag, to make it easier to produce an R wrapper.
  • All code now compiles cleanly with "-std=c89 -Wall -Werror".

Logo python weka wrapper3 0.1.2

by fracpete - January 4, 2017, 10:27:40 CET [ Project Homepage BibTeX Download ] 1813 views, 321 downloads, 3 subscriptions

About: A thin Python3 wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:
  • "typeconv.double_matrix_to_ndarray" no longer assumes a square matrix (https://github.com/fracpete/python-weka-wrapper3/issues/4)
  • "len(Instances)" now returns the number of rows in the dataset (module "weka.core.dataset")
  • added method "insert_attribute" to the "Instances" class
  • added class method "create_relational" to the "Attribute" class
  • upgraded Weka to 3.9.1

Showing Items 11-20 of 635 on page 2 of 64: Previous 1 2 3 4 5 6 7 Next Last