In many areas of
information science, finding predictive relationships from
data is a very important task. Initial discovery of relationships is usually done with a
training set while a
test set and
validation set are used for evaluating whether the discovered relationships hold. More formally, a
training set is a set of
data used to discover potentially predictive relationships. A
test set is a set of
data used to assess the strength and utility of a predictive relationship. Test and training sets are used in
intelligent systems,
machine learning,
genetic programming and
statistics.