The results can be saved either in ARFF or CSVformats or as a JDBC database.Īlso, you can analyze and test a data file. Also, you have to choose the desired dataset and algorithm and then you can run it. You just have to configure your experiment by choosing its type: classification or regression. The program is also suitable for developing new machine learning schemes. Furthermore, you can use it for data plotting, as it allows you to view and analyze point graphs for each possible attribute combination. In addition to this, the program also includes tools for data clustering, association rules and attributes evaluator. ![]() Also, you can classify the available data according to a predefined set of rules, as well as perform a complete cost / benefit analysis that automatically displays the cost matrix and the threshold curve. You can filter the data contents, change the attributes and visualize the result in a bar chart. The first section allows you to open a dataset or a database and edit it as you wish. When running the program, you can view four available applications that you can access: 'Explorer', 'Experimenter', 'KnowledgeFlow' and 'Simple CLI'. The algorithms that Weka provides can be applied directly to a dataset or your Java code. Weka is a package that offers users a collection of learning schemes and tools that they can use for data mining. Data mining is a field that implies analyzing large data sets in order to discover new patterns and methods for database management, data processing and inference considerations.
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