TELKOMNIKA Telecommunication, Computing, Electronics and Control
A new model for large dataset dimensionality reduction based on teaching learning-based optimization and logistic regression
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
A new model for large dataset dimensionality reduction based on teaching learning-based optimization and logistic regression
A new model for large dataset dimensionality reduction based on teaching learning-based optimization and logistic regression
Subject
Feature selection, FSS, IDS, NTLBO, Subset, TLBO
Description
One of the human diseases with a high rate of mortality each year is breast cancer (BC). Among all the forms of cancer, BC is the commonest cause of death among women globally. Some of the effective ways of data classification are data mining and classification methods. These methods are particularly efficient in the medical field due to the presence of irrelevant and redundant attributes in medical datasets. Such redundant attributes are not needed to obtain an accurate estimation of disease diagnosis. Teaching learning-based optimization (TLBO) is a new metaheuristic that has been successfully applied to several intractable optimization problems in recent years. This paper
presents the use of a multi-objective TLBO algorithm for the selection of
feature subsets in automatic BC diagnosis. For the classification task in this work, the logistic regression (LR) method was deployed. From the results, the projected method produced better BC dataset classification accuracy (classified into malignant and benign). This result showed that the projected TLBO is an efficient features optimization technique for sustaining data-based decision-making systems.
presents the use of a multi-objective TLBO algorithm for the selection of
feature subsets in automatic BC diagnosis. For the classification task in this work, the logistic regression (LR) method was deployed. From the results, the projected method produced better BC dataset classification accuracy (classified into malignant and benign). This result showed that the projected TLBO is an efficient features optimization technique for sustaining data-based decision-making systems.
Creator
Hind Raad Ibraheem, Zahraa Faiz Hussain, Sura Mazin Ali, Mohammad Aljanabi, Mostafa Abdulghafoor Mohammed, Tole Sutikno
Source
DOI: 10.12928/TELKOMNIKA.v18i3.13764
Publisher
Universitas Ahmad Dahlan
Date
June 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Hind Raad Ibraheem, Zahraa Faiz Hussain, Sura Mazin Ali, Mohammad Aljanabi, Mostafa Abdulghafoor Mohammed, Tole Sutikno, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
A new model for large dataset dimensionality reduction based on teaching learning-based optimization and logistic regression,” Repository Horizon University Indonesia, accessed November 21, 2024, https://repository.horizon.ac.id/items/show/3802.
A new model for large dataset dimensionality reduction based on teaching learning-based optimization and logistic regression,” Repository Horizon University Indonesia, accessed November 21, 2024, https://repository.horizon.ac.id/items/show/3802.