Weka for Mac is a collection of machine learning algorithms for solving real-world data mining problems.The algorithms can
Weka for Mac is a collection of machine learning algorithms for solving real-world data mining problems.The algorithms can either be applied directly to a data set or called from your own Java code. It contains the tools you'll need for data pre-processing, classification, regression, clustering, association rules, and visualization. The application is also appropriate for developing new machine learning schemes.Key features include:
- Machine learning.
- Data mining.
- Pre-processing.
- Classification.
- Regression.
- Clustering.
- Association rules.
- Attribute selection.
- Experiments.
- Workflow.
- Visualization.
Weka for Mac's collection of algorithms range from those that handle data pre-processing to modeling. The core data mining algorithms include regression, clustering and classification. Although Weka for Mac has a full suite of algorithms for data analysis, it has been built to handle data as single flat files. Subsequently, it does not handle multi-relational mining and sequence modeling.
Weka for Mac runs on
Mac
and is available under the
OpenSource under LGPL
license
— the installer is 118.40 MB.
We’ve catalogued it under
Editors.
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