Journal of Physics Conference Series · 2019 · 10 citations · 0 references
Search OptimizationEngineeringMachine LearningFeature SelectionFeature ExtractionClassification MethodInformation RetrievalData ScienceData MiningPattern RecognitionInformative Heuristic CriteriaFeature EngineeringKnowledge DiscoveryIntelligent ClassificationComputer ScienceStatistical Pattern RecognitionFeature ConstructionHeuristic CriteriaPopular CriteriaClassificationPattern Recognition Application
Abstract At present the most popular criteria are of informative heuristic criteria associated with the estimation of separability given classes and based on the fundamental pattern recognition compactness hypothesis: with increasing distance between the classes improved their separability. “Good” are those features that maximize the relationship. Such heuristic criteria, although are widely used in solving practical problems of classification, but in theory are scarcely explored. At present, the method of selecting informative features, taking into account the relationships of features based on heuristic criteria, has not been developed. The report considers this task.