Weka Machine Learning Group, University of Waikato, Hamilton, NZ
winget install --id=UniversityOfWaikato.Weka -e Weka is a collection of machine learning algorithms for solving real-world data mining problems. It is written in Java and runs on almost any platform. The algorithms can either be applied directly to a dataset or called from your own Java code.
Weka is a collection of machine learning algorithms designed to address real-world data mining challenges. It provides a robust platform for applying various techniques such as classification, clustering, and regression directly to datasets or integrating them into custom Java applications.
Key Features:
- Open-source software distributed under the GNU General Public License (GPL).
- Cross-platform compatibility due to its Java-based architecture.
- Extensive library of machine learning algorithms covering tasks like classification, clustering, data mining, and regression.
- Flexible integration capabilities, allowing users to apply algorithms directly or embed them into their own code.
- User-friendly workbench for exploring and experimenting with different techniques.
Audience & Benefit: Ideal for data scientists, machine learning engineers, researchers, and educators seeking a versatile toolset for analysis, teaching, and innovation. Weka’s open-source nature and extensive algorithm support enable users to efficiently tackle complex data mining tasks while fostering collaboration and experimentation within the machine learning community. It can be installed via winget, ensuring seamless integration into your workflow.