This article explains the various terms that are used throughout the rest of the tutorials and are also used in the source-code documentation.
We also assume you have at the very least a basic knowledge of Java, the language in which the library is written.
In short every data sample is stored in an Instance, which are grouped together in a Dataset. Each Instance can have a number of attributes that have real values. The terms features and attributes are synonymous in this context.
Each Instance can have a class label. Algorithms are functions that work on Datasets and Instances. Classification algorithms for example can be trained on a Dataset and can later be applied to classify Instances.
More in detail: