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 …

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 …

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 …

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 …

Online shop** 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 …

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 …

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 …

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 …

Stacked ensemble formulates an ensemble using a meta-learner to combine (stack) the
predictions of multiple base classifiers. It suffers from the problem of suboptimal performance …

Öz Yazılım hata tahmini, kaynak kodda bulunan olası hataların (veya kusurların) varlığını
tahmin etmek için sınıflandırma ve/veya regresyon algoritmalarının kullanımı işlemidir. Fakat …