Weka (Waikato Environment for Knowledge Analysis) is a comprehensive popular suite of machine learning software, developed at the University of Waikato, New Zealand. It is a collection of machine learning algorithms for solving real-world data mining problems including decision trees, support vector machines, instance-based classifiers, Bayes decision schemes, neural networks etc. and clustering.
The algorithms can either be applied directly to a dataset or called from your own Java code.
The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modeling, together with graphical user interfaces for easy access to this functionality.
Key Features
- Provides an environment with algorithms for data preprocessing, feature selection, classification, regression, and clustering.
- Graphical user interface that makes applying machine learning algorithms easy
- Four graphical user interface modules:
- Explorer.
- Experimenter.
- Knowledge Flow.
- Simple Command Line Interface.
- Four graphical user interface modules:
- Schemes for classification include:
- Decision trees, rule learners, naive Bayes, decision tables, locally weighted regression, SVMs, instance-based learners, logistic regression, voted perceptrons, multi-layer perceptron.
- Schemes for numeric prediction include:
- Lnear regression, model tree generators, locally weighted regression, instance-based learners, decision tables, multi-layer perceptron.
- Meta-schemes include:
- Bagging, boosting, stacking, regression via classification, classification via regression, cost sensitive classification.
- Schemes for clustering:
- EM and Cobweb.
- Schemes for feature selection.
- Provides implementations of learning algorithms:
- Classification.
- Clustering.
- Association Rule Mining.
- Attribute Selection.
- General API to embed WEKA in other applications.
Website: www.cs.waikato.ac.nz/ml/weka
Support:
Developer: University of Waikato
License: GNU General Public License v2.0
Weka is written in Java. Learn Java with our recommended free books and free tutorials.
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| KNIME | Konstanz Information Miner |
| Weka | Waikato Environment for Knowledge Analysis |
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| Rattle | Gnome cross platform GUI for Data Mining using R |
Read our verdict in the software roundup.
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