A neighborhood undersampling stacked ensemble (NUS-SE) in imbalanced classification

Z Seng, SA Kareem, KD Varathan - Expert Systems with Applications, 2021 - Elsevier
Stacked ensemble, which formulates an ensemble by using a meta-learner to combine
(stack) the predictions of multiple base classifiers, suffers from the problem of suboptimal …

An empirical evaluation of stacked ensembles with different meta-learners in imbalanced classification

S Zian, SA Kareem, KD Varathan - IEEE Access, 2021 - ieeexplore.ieee.org
The selection of a meta-learner determines the success of a stacked ensemble as the meta-
learner is responsible for the final predictions of the stacked ensemble. Unfortunately, in …

CSSG: A cost‐sensitive stacked generalization approach for software defect prediction

Z Eivazpour, MR Keyvanpour - Software Testing, Verification …, 2021 - Wiley Online Library
The prediction of software artifacts on defect‐prone (DP) or non‐defect‐prone (NDP) classes
during the testing phase helps minimize software business costs, which is a classification …

Data mining and machine learning for software engineering

EO Kiyak - Data Mining-Methods, Applications and Systems, 2020 - books.google.com
Software engineering is one of the most utilizable research areas for data mining.
Developers have attempted to improve software quality by mining and analyzing software …

Improving the effectiveness of classification using the data level approach and feature selection techniques in online shoppers purchasing intention prediction

I Kurniawan, MF Akbar, DF Saepudin… - Journal of Physics …, 2020 - iopscience.iop.org
Online shopping is a form of trading using electronic devices that allows consumers to buy
goods or services from sellers via the internet. Other names for these activities are: e-web …

An ordinal classification approach for software bug prediction

E Öztürk, KU Birant, D Birant - Dokuz Eylül Üniversitesi Mühendislik …, 2019 - dergipark.org.tr
Software bug prediction is the process of utilizing classification and/or regression algorithms
to predict the presence of possible errors (or defects) in a source code. However, current …

A Clustering Resampling Stacked Ensemble Method for Imbalance Classification Problem

J Li, J Du, X Zhang - 2022 IEEE 24th Int Conf on High …, 2022 - ieeexplore.ieee.org
The results of the existing research on ensemble methods based on resampling are the best
for the imbalance classification task, whereas the results of independent use of resampling …

A Kernel Density Estimation-Based Variation Sampling for Class Imbalance in Defect Prediction

Y Zhang, X Yan, AA Khan - 2020 IEEE Intl Conf on Parallel & …, 2020 - ieeexplore.ieee.org
In software engineering, software defect prediction can help to discover the defect modules
and improve the quality of software products. However, class imbalance makes the …

[PDF][PDF] MENGATASI IMBALANCE CLASS DAN MENINGKATKAN EFEKTIVITAS KLASIFIKASI MENGGUNAKAN TEKNIK PENDEKATAN LEVEL DATA DAN TEKNIK …

I KURNIAWAN, N MANDIRI - repository.bsi.ac.id
Demikianlah surat pernyataan ini saya buat dengan sebenar-benamya. Apabila dikemudian
hari temyata saya memberikan keterangan palsu dan atau ada pihak lain yang mengklaim …

[PDF][PDF] DEWAN PENGUJI

D Riana, M MM - repository.bsi.ac.id
Teknologi semakin mengubah tren berbelanja. Pengalaman pembelian konsumen telah
ditransformasikan tidak hanya oleh Web, tetapi juga oleh kemajuan baru dalam perangkat …