This is a git mirror of the The University of Waikato machine learning project WEKA.
Weka alternatives and similar libraries
Based on the "Machine Learning" category.
Alternatively, view Weka alternatives based on common mentions on social networks and blogs.
9.9 10.0 Weka VS Apache SparkApache Spark - A unified analytics engine for large-scale data processing
9.6 9.9 L1 Weka VS Deeplearning4jModel import deployment framework for retraining models (pytorch, tensorflow,keras) deploying in JVM Micro service environments, mobile devices, iot, and Apache Spark
7.3 1.7 L4 Weka VS Oryx 2Oryx 2: Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning
7.2 9.7 Weka VS Deep Java Library (DJL)An Engine-Agnostic Deep Learning Framework in Java
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
Do you think we are missing an alternative of Weka or a related project?
Computing and Mathematical Sciences at the University of Waikato now has an official github organization including a read-only git mirror of Weka's subversion repository. Therefore, this repo is no longer necessary and will one day be removed. In the meantime, please follow the Waikato repo for the most up-to-date and official changes. Additionally, Waikato also maintain a curated list of repositories you may find interesting. Enjoy.
(Official README) WEKA (developer version)
Read-only git mirror of Weka's subversion repository.
The official WEKA source code of the developer version is available from this URL:
Contributions and bug fixes an be contributed as patch file and posted to the WEKA mailing list.
A few notes from the unofficial mirror
NOTE The owner of this repository has no affiliation with official
WEKA project. This repo is periodically updated as a kindness to others who
have shown interest in it. It can take several hours to
checkout the full
official WEKA subversion repository and several minutes just to update with any
new commits. Therefore, this exists to provide an easy way to access and peruse
the WEKA source using git, nothing more.
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
The official WEKA source code is hosted using subversion at the Waikato SVN server.
The current version of WEKA is licensed under the GNU General Public license version 3.0.
Use the weka-trunk branch to follow the official code base under active development at the University of Waikato.
*Note that all licence references and agreements mentioned in the Weka README section above are relevant to that project's source code only.