Associate: to learn association rules for the data.Cluster: to learn clusters for the data.Classify: to train and test learning schemes that classify or perform regression.
Preprocess: which enables you to choose and modify the data being acted on.2- Explorer:Īn environment for exploring data with WEKA. It offers a simple Weka shell with separated commandline and output.
WEKA FOR MAC FREE DOWNLOAD FULL
Provides full access to all Weka classes, i.e., classifiers, filters, clusterers, etc., but without the hassle of the CLASSPATH. Weka 3.8 and 3.9 feature a package management system that makes it easy for the Weka community to add new functionalities to Weka. Stable versions receive only bug fixes, while the development version receives new features. For the bleeding edge, it is also possible to download nightly snapshots. There are two versions of Weka: Weka 3.8 is the latest stable version and Weka 3.9 is the development version. This tool doesn’t support processing of related charts however, there are many tools allowing combining separate charts into a single chart, which can be loaded right into Weka. Weka provides access to SQL databases using Java Database Connectivity (JDBC) and allows using the response for an SQL query as the source of data.
Weka is open source software released under the GNU General Public License. It is written in Java and developed at the University of Waikato, New Zealand. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization. WEKA (Waikato Environment for Knowledge Analysis) is a collection of machine learning algorithms for data mining tasks.
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