This paper presents a learning system that uses genetic programming as a tool for automatically inferring the set of classification rules to be used during a preclassification sta...
Claudio De Stefano, Antonio Della Cioppa, Angelo M...
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Linear Discriminant Analysis (LDA) is a well-known scheme for supervised subspace learning. It has been widely used in the applications of computer vision and pattern recognition....
In the present paper, we introduce a variant of Gold-style learners that is not required to infer precise descriptions of the languages in a class, but that must find descriptive ...
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...