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Scopus YÖKSİS DOI Eşleşti SJR Q1

Boosting the oversampling methods based on differential evolution strategies for imbalanced learning

Applied Soft Computing · Kasım 2021

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YÖKSİS Kayıtları
Boosting the oversampling methods based on differential evolution strategies for imbalanced learning
Applied Soft Computing · 2021 SCI-Expanded
Doç. Dr. AHMET CEVAHİR ÇINAR →
Boosting the oversampling methods based on differential evolution strategies for imbalanced learning
APPLIED SOFT COMPUTING · 2021 SCI-Expanded
Doç. Dr. MEHMET AKİF ŞAHMAN →
YÖKSİS ISSN Eşleşmesi

Bu dergide (ISSN eşleşmesi) kurumun 17 kaydı bulundu.

YÖKSİS Kayıtları — ISSN Eşleşmesi
Detection of abnormalities in lumbar discs from clinical lumbar MRI with hybrid models
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Color image segmentation based on multiobjective artificial bee colony optimization
2015 ISSN: 15684946 SCI-Expanded
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Color image segmentation based on multiobjective artificial bee colony optimization
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Liver fibrosis staging using CT image texture analysis and soft computing
2014 ISSN: 15684946 SCI-Expanded
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New Approaches to determine Age and Gender in Image Processing Techniques using Multilayer Perceptron Neural Network
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A modification of tree-seed algorithm using Deb’s rules for constrained optimization
2018 ISSN: 1568-4946 SCI Q1
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A hybrid binary grey wolf optimizer for selection and reduction of reference points with extreme learning machine approach on local GNSS/leveling geoid determination
2021 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. KEMAL TÜTÜNCÜ →
Boosting the oversampling methods based on differential evolution strategies for imbalanced learning
2021 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. AHMET CEVAHİR ÇINAR →
A discrete spotted hyena optimizer for solving distributed job shop scheduling problems
2021 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. MEHMET AKİF ŞAHMAN →
A hybrid binary grey wolf optimizer for selection and reduction of reference points with extreme learning machine approach on local GNSS/leveling geoid determination
2021 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. MEHMET AKİF ŞAHMAN →
Boosting the oversampling methods based on differential evolution strategies for imbalanced learning
2021 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. MEHMET AKİF ŞAHMAN →
Classification rule mining based on Pareto-based Multiobjective Optimization
2022 ISSN: 1568-4946 SCI-Expanded Q1
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Classification rule mining based on Pareto-based Multiobjective Optimization
2022 ISSN: 1568-4946 SCI-Expanded Q1
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Image forgery detection by combining Visual Transformer with Variational Autoencoder Network
2024 ISSN: 1568-4946 SCI-Expanded Q1
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Parametric picture fuzzy cross-entropy measures based on d-Choquet integral for building material recognition Applied Soft Computing
2024 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. DİLEK SÖYLEMEZ ÖZDEN →
A synergistic oversampling technique with differential evolution and safe level synthetic minority oversampling
2025 ISSN: 1568-4946 SCI-Expanded
Doç. Dr. AHMET CEVAHİR ÇINAR →
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Makale Bilgileri

Dergi Applied Soft Computing
ISSN15684946
Yayın TarihiKasım 2021
Cilt / Sayfa112
DOI10.1016/j.asoc.2021.107787
Scopus ID2-s2.0-85113352660
Özet The class imbalance problem is a challenging problem in the data mining area. To overcome the low classification performance related to imbalanced datasets, sampling strategies are used for balancing the datasets. Oversampling is a technique that increases the minority class samples in various proportions. In this work, these 16 different DE strategies are used for oversampling the imbalanced datasets for better classification. The main aim of this work is to determine the best strategy in terms of Area Under the receiver operating characteristic (ROC) Curve (AUC) and Geometric Mean (G-Mean) metrics. 44 imbalanced datasets are used in experiments. Support Vector Machines (SVM), k-Nearest Neighbor (kNN), and Decision Tree (DT) are used as a classifier in the experiments. The best results are produced by 6th Debohid Strategy (DSt6), 1th Debohid Strategy (DSt1), and 3th Debohid Strategy (DSt3) by using kNN, DT, and SVM classifiers, respectively. The obtained results outperform the 9 state-of-the-art oversampling methods in terms of AUC and G-Mean metrics

Yazarlar (4)

1
Sedat Korkmaz
2
Mehmet Akif Şahman
3
Ahmet Cevahir Cinar
4
Ersin Kaya

Anahtar Kelimeler

Class imbalance Differential evolution Differential evolution strategies Imbalanced datasets Imbalanced learning Oversampling

Kurumlar

Konya Technical University
Konya Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Applied Soft Computing
Q1
SJR Skoru1,511
H-Index208
YayıncıElsevier B.V.
ÜlkeNetherlands
Software (Q1)
Dergi sayfasına git

Metrikler

26
Atıf
4
Yazar
6
Anahtar Kelime

Sistemimizdeki Yazarlar

AÇ
AHMET CEVAHİR ÇINAR
Doç. Dr.

Hızlı Erişim

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