Публікація:
Adaptive human machine interaction approach for feature selection-extraction task in medical data mining

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Дата

2018

Назва журналу

ISSN журналу

Назва тома

Видавництво

International Journal of Computing

Дослідницькі проекти

Організаційні підрозділи

Видання журналу

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.

DOI