Weka is an open-source project in machine learning, Data Mining.
Weka is a comprehensive collection of machine-learning algorithms for data mining tasks written in Java.
The algorithms can either be applied directly to a dataset or called from your own Java code.
Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization.
The more_options menu on the Classify panel can be used to customized the output. Depending on the setup, Weka will generate one or more of the following sections:
When using cross-validation, Weka prints a model built on the full dataset. The statistics, however, are calculated from the various train/test splits. This can be confusing, because the model stay the same regardless of the number of folds or the value of the random seed.
The more_options menu on the Classify panel gives the following options: