Публікація: Adaptive human machine interaction approach for feature selection-extraction task in medical data mining
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Дата
2018
Автори
Назва журналу
ISSN журналу
Назва тома
Видавництво
International Journal of Computing
Анотація
Feature Selection task is one of the most complicated and actual in the
areas of Data Mining and Human Machine Interaction. Many approaches to its
solving are based on non-mathematical and presentative hypothesis. New
approach to evaluation of medical features information quantity, based on
optimized combination of feature selection and feature extraction methods is
proposed. This approach allows us to produce optimal reduced number of
features with linguistic interpreting of each of them. Hybrid system of feature
selection/extraction based on Neural Network-Physician interaction is
investigated. This system is numerically simple, can produce feature
selection/extraction with any number of factors in online mode using neural
network-physician interaction based on Oja’s neurons for online principal
component analysis and calculating distance between first principal component
and all input features. A series of experiments confirms efficiency of proposed
approaches in Medical Data Mining area and allows physicians to have the most
informative features without losing their linguistic interpreting.
Опис
Ключові слова
Human Machine Interaction, feature selection, feature extraction, Medical Data Mining, Oja’s neuron, Neural Network Approach
Бібліографічний опис
Perova I. Adaptive human machine interaction approach for feature selection-extraction task in medical data mining / I. Perova, Ye. Bodyanskiy // International Journal of Computing. - 2018.-17 (2). - P. 113-119.