Learning by precedents based on the analysis of the features properties - V. V. Krasnoproshin; V. G. Rodchanka (Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki)
The issue of learning by precedents is studied. A method of learning based on the analysis of the properties of feature combinations and building feature subspaces where classes do not intersect is proposed. An algorithm that allows paralleling of the learning process and performing it in the automatic mode has been developed in this approach. A possibility to use this method for automatic detection and interpretation of hidden, previously unknown patterns in data mining tasks is presented.