In a majority–minority classification problem, class imbalance in the dataset (s) can
dramatically skew the performance of classifiers, introducing a prediction bias for the …

The treatment decisions for patients with hepatocellular carcinoma are determined by a wide
range of factors, and there is a significant difference between the recommendations of …

High class imbalance between majority and minority classes in datasets can skew the
performance of Machine Learning algorithms and bias predictions in favor of the majority …

Software defect prediction (SDP) is a technique that uses known software features and
defect information to predict target software defects. It helps reduce software development …

Effective prediction of software modules, those that are prone to defects, will enable software
developers to achieve efficient allocation of resources and to concentrate on quality …

Satellite-derived bathymetry (SDB) is an effective means of obtaining global shallow water
depths. However, the effect of inherent optical properties (IOPs) on the accuracy of SDB …

Class imbalance exists in many classification problems, and since the data is designed for
accuracy, imbalance in data classes can lead to classification challenges with a few classes …

Software fault prediction (SFP) is an active issue in software engineering (SE). At present,
machine learning (ML) has been successfully applied to SFP classification problems …

The main goal of software quality engineering is to produce a high-quality software product
through the use of various techniques and processes. Classification models are effective …

Feature selection is a key challenge before the process of classification could be performed.
The classification accuracy would increase by using a good feature selection method and …