Priority: optional
Section/category: contrib/science
Installed size: 4740
Maintainer(s): Soeren Sonnenburg
Architecture (arch): all
Source:
Version in APT: 3.5.7+tut1-1
Provides:
Depends: sun-java6-jre
Pre-depends:
Recommends:
Filename: pool/contrib/w/weka/weka_3.5.7+tut1-1_all.deb
Filesize: 4740
MD5 Hash: 0e09780abf8db3cefe583000f90eca74
Description: Machine learning algorithms for data mining tasks
Weka is a collection of machine learning algorithms in Java that can
either be used from the command-line, or called from your own Java
code. Weka is also ideally suited for developing new machine learning
schemes.
.
Implemented schemes cover decision tree inducers, rule learners, model
tree generators, support vector machines, locally weighted regression,
instance-based learning, bagging, boosting, and stacking. Also included
are clustering methods, and an association rule learner. Apart from
actual learning schemes, Weka also contains a large variety of tools
that can be used for pre-processing datasets.
.
This package contains the binaries and examples.
Homepage: http://www.cs.waikato.ac.nz/~ml/weka/
1. Weka 3 - Data Mining with Open Source Machine Learning Software in ...
Weka 3: Data Mining Software in Java GNU General Public License. Pentaho's live forum for Weka forum for interaction among Weka project community members.
http://www.cs.waikato.ac.nz/~ml/weka/
2. weka.classifiers
Interface Summary; IterativeClassifier: Interface for classifiers that can induce models of growing complexity one step at a time. Sourcable: Interface for classifiers that can be ...
http://weka.sourceforge.net/doc/weka/classifiers/package-summary.html
3. weka.classifiers.functions
Class Summary; LeastMedSq: Implements a least median sqaured linear regression utilising the existing weka LinearRegression class to form predictions.
http://weka.sourceforge.net/doc/weka/classifiers/functions/package-summary.html