Weka system brings together cutting-edge machine learning algorithms and data pre-processing tools so that users can quickly and flexibly apply existing mature processing methods to new data sets.
1, Processing Method
includes all methods for dealing with standard data mining problems: regression, classification, clustering, association rules, and attribute selection.
2 Input data
- Enter the file represented by ARFF format
- directly read the database table
3, Weka main interface Weka GUI Chooser
(1) ExplorerGraphic user interface, you can call all the features of Weka by selecting menus and filling out forms.
(2)KnowledgeFlowUsing an incremental (batch) approach to processing large data sets, users can customize the way and order in which the data streams are processed. The components representing the data source, the preprocessing tool, the learning algorithm, the evaluation means, and the visualization module are combined in a certain order to form a data stream.
(3)ExperimenterHelps users answer a basic question encountered in practical application classification and regression techniques.
(4)Simple CLI(|Simple CLI)This interface is used to interact with the user and can execute the Weka command directly.