Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree

The problem of developing universal classifiers of biomedical data, in particular those that characterize the presence of a large number of parameters, inaccuracies and uncertainty, is urgent. Many studies are aimed at developing methods for analyzing these data, among them there are methods based o...

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Autores principales:	Lyudmila Dobrovska, Olena Nosovets
Formato:	article
Lenguaje:	EN RU UK
Publicado:	PC Technology Center 2021
Materias:	neural network multilayer perceptron using a genetic algorithm cart decision tree Technology (General) T1-995 Industry HD2321-4730.9
Acceso en línea:	https://doaj.org/article/88fa0e7e710d4351aa8f75fbc0492dcc
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id	oai:doaj.org-article:88fa0e7e710d4351aa8f75fbc0492dcc
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spelling	oai:doaj.org-article:88fa0e7e710d4351aa8f75fbc0492dcc2021-11-04T14:13:12ZDevelopment of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree1729-37741729-406110.15587/1729-4061.2021.242795https://doaj.org/article/88fa0e7e710d4351aa8f75fbc0492dcc2021-10-01T00:00:00Zhttp://journals.uran.ua/eejet/article/view/242795https://doaj.org/toc/1729-3774https://doaj.org/toc/1729-4061The problem of developing universal classifiers of biomedical data, in particular those that characterize the presence of a large number of parameters, inaccuracies and uncertainty, is urgent. Many studies are aimed at developing methods for analyzing these data, among them there are methods based on a neural network (NN) in the form of a multilayer perceptron (MP) using GA. The question of the application of evolutionary algorithms (EA) for setting up and learning the neural network is considered. Theories of neural networks, genetic algorithms (GA) and decision trees intersect and penetrate each other, new developed neural networks and their applications constantly appear. An example of a problem that is solved using EA algorithms is considered. Its goal is to develop and research a classifier for the diagnosis of breast cancer, obtained by combining the capabilities of the multilayer perceptron using the genetic algorithm (GA) and the CART decision tree. The possibility of improving the classifiers of biomedical data in the form of NN based on GA by applying the process of appropriate preparation of biomedical data using the CART decision tree has been established. The obtained results of the study indicate that these classifiers show the highest efficiency on the set of learning and with the minimum reduction of Decision Trees; increasing the number of contractions usually degrades the simulation result. On two datasets on the test set, the simulation accuracy was »83–87 %. The experiments carried out have confirmed the effectiveness of the proposed method for the synthesis of neural networks and make it possible to recommend it for practical use in processing data sets for further diagnostics, prediction, or pattern recognitionLyudmila DobrovskaOlena NosovetsPC Technology Centerarticleneural networkmultilayer perceptron using a genetic algorithmcart decision treeTechnology (General)T1-995IndustryHD2321-4730.9ENRUUKEastern-European Journal of Enterprise Technologies, Vol 5, Iss 9 (113), Pp 82-90 (2021)
institution	DOAJ
collection	DOAJ
language	EN RU UK
topic	neural network multilayer perceptron using a genetic algorithm cart decision tree Technology (General) T1-995 Industry HD2321-4730.9
spellingShingle	neural network multilayer perceptron using a genetic algorithm cart decision tree Technology (General) T1-995 Industry HD2321-4730.9 Lyudmila Dobrovska Olena Nosovets Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree
description	The problem of developing universal classifiers of biomedical data, in particular those that characterize the presence of a large number of parameters, inaccuracies and uncertainty, is urgent. Many studies are aimed at developing methods for analyzing these data, among them there are methods based on a neural network (NN) in the form of a multilayer perceptron (MP) using GA. The question of the application of evolutionary algorithms (EA) for setting up and learning the neural network is considered. Theories of neural networks, genetic algorithms (GA) and decision trees intersect and penetrate each other, new developed neural networks and their applications constantly appear. An example of a problem that is solved using EA algorithms is considered. Its goal is to develop and research a classifier for the diagnosis of breast cancer, obtained by combining the capabilities of the multilayer perceptron using the genetic algorithm (GA) and the CART decision tree. The possibility of improving the classifiers of biomedical data in the form of NN based on GA by applying the process of appropriate preparation of biomedical data using the CART decision tree has been established. The obtained results of the study indicate that these classifiers show the highest efficiency on the set of learning and with the minimum reduction of Decision Trees; increasing the number of contractions usually degrades the simulation result. On two datasets on the test set, the simulation accuracy was »83–87 %. The experiments carried out have confirmed the effectiveness of the proposed method for the synthesis of neural networks and make it possible to recommend it for practical use in processing data sets for further diagnostics, prediction, or pattern recognition
format	article
author	Lyudmila Dobrovska Olena Nosovets
author_facet	Lyudmila Dobrovska Olena Nosovets
author_sort	Lyudmila Dobrovska
title	Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree
title_short	Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree
title_full	Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree
title_fullStr	Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree
title_full_unstemmed	Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree
title_sort	development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree
publisher	PC Technology Center
publishDate	2021
url	https://doaj.org/article/88fa0e7e710d4351aa8f75fbc0492dcc
work_keys_str_mv	AT lyudmiladobrovska developmentoftheclassifierbasedonamultilayerperceptronusinggeneticalgorithmandcartdecisiontree AT olenanosovets developmentoftheclassifierbasedonamultilayerperceptronusinggeneticalgorithmandcartdecisiontree
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Development of the classifier based on a multilayer perceptron using genetic algorithm and cart decision tree

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