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Thread: Weka 3.6.7 and 3.7.6 releases

  1. #1
    Join Date
    Aug 2006
    Posts
    1,411

    Thumbs up Weka 3.6.7 and 3.7.6 releases

    Hi everyone!

    New versions of Weka are available for download from the Weka homepage:

    * Weka 3.6.7 - stable book 3rd edition version. It is available as ZIP, with Win32 installer, Win32 installer incl. JRE 1.6.0_32, Win64 installer, Win64 installer incl. 64 bit JRE 1.6.0_32 and Mac OS X application.

    * Weka 3.7.6 - development version. It is available as ZIP, with Win32 installer, Win32 installer incl. JRE 1.6.0_32, Win64 installer, Win64 installer incl. 64 bit JRE 1.6.0_32 and Mac OS X application.

    Both versions contain a significant number of bugfixes, it is recommended to upgrade to the new versions. Stable Weka 3.6 receives bug fixes only. The development version receives bug fixes and new features.

    Weka homepage:
    http://www.cs.waikato.ac.nz/~ml/weka/

    Pentaho data mining community documentation:
    http://wiki.pentaho.com/display/Pent...+Documentation

    Packages for Weka>=3.7.2 can be browsed online at:
    http://weka.sourceforge.net/packageMetaData/

    The Pentaho Weka micro site at http://weka.pentaho.com/ will be updated to reflect the new releases soon.

    Note:
    It might take a while before Sourceforge.net has propagated all the files to its mirrors.

    What's new in 3.7.6?

    Some highlights
    ---------------

    In core weka:

    * Weka 3.7 is now GPL 3.0.
    * Weka releases now available on Maven central
    * Logistic now has an option to use conjugate gradient descent rather than quasi-Newton with BFGS updates.
    * weka.classifiers.bayes.NaiveBayesMultinomialText - naive Bayes multinomial classifier that operates directly on string attributes.
    * Appender component for the Knowledge Flow that can append sets of instances together.
    * SubstringLabeler component for the Knowledge Flow that can use substring or regex matching on string attribute values to assign various user defined nominal values to a new "label" attribute.
    * SubstringReplacer component for the Knowledge Flow that can replace substrings or regex matches with user supplied strings in string attribute values.
    * Sorter component for the Knowledge Flow that implements a streaming merge sort that writes a sorted in-memory buffer to a file when full. Can sort descending or ascending on multiple attributes.
    * DatabaseSaver can now truncate the target table if desired.
    * Area under the precision-recall curve evaluation metric.
    * Package manager's cache refresh mechanism is now much faster.
    * Package manager now checks for new versions of existing packages on the server as well as entirely new packages.
    * Random forest now has an option to print all the ensemble trees as part of its output.


    In packages:
    * cascadeKMeans package - weka.clusterers.CascadeSimpleKMeans, contributed by Martin Guetlein.
    * weka.classifiers.functions.RBFRegressor added to the RBFNetwork package
    * jsonFieldExtractor package - Knowledge Flow step to extract one or more fields from repeating blocks of JSON text into new attributes.


    As usual, for a complete list of changes refer to the changelogs.

    Cheers,
    The Weka Team
    Last edited by Mark; 05-10-2012 at 11:24 PM.

  2. #2
    Join Date
    Nov 2012
    Posts
    1

    Default

    Cheers Weka Team just want to tell you i love your work .... Weka 3.7.6 RULES i love using it....
    cna classes online
    Last edited by ciprian21; 11-29-2012 at 09:15 AM.

  3. #3

    Default

    It is an great data mining tool.
    is the extreme learing algorithm available in Weka.
    if not , is there any package that offer this algorithm.
    thanks in advance.

  4. #4
    Join Date
    Aug 2006
    Posts
    1,411

    Default

    Hi,

    No, I'm afraid that Weka does not have an implementation of the extreme learning algorithm. There are other feed-forward neural network implementations available in Weka though.

    Cheers,
    Mark.

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