A number of learning algorithms purpose at identifying much better representations on the inputs supplied during training.[61] Basic examples consist of principal ingredient analysis and cluster analysis. Attribute learning algorithms, also referred to as representation learning algorithms, often attempt to protect the knowledge within their input