Optimized decision forest for website phishing detection

AO Balogun, HA Mojeed, KS Adewole… - Data Science and …, 2021 - Springer
The development of web and internet technology has resulted in its application in a wide
range of services. This has resulted in an increase in the number of cybersecurity issues …

Software Defects Prediction At Method Level Using Ensemble Learning Techniques

AM Ibrahim, H Abdelsalam… - International Journal of …, 2023 - journals.ekb.eg
Creating error-free software artifacts is essential to increase software quality and potential re-
usability. However, testing software artifacts to find defects and fix them is time-consuming …

Rotation forest-based logistic model tree for website phishing detection

AO Balogun, NO Akande, FE Usman-Hamza… - … Science and Its …, 2021 - Springer
The emergence of web and internet technology has led to its use in a broad array of services
ranging from financial to educational services. This has led to a spike in the number of …

[HTML][HTML] Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction

FE Usman-Hamza, AO Balogun, RT Amosa… - Scientific African, 2024 - Elsevier
In recent times, customer churn has become one of the most significant issues in business-
oriented sectors with telecommunication being no exception. Maintaining current customers …

A Novel Rank Aggregation‐Based Hybrid Multifilter Wrapper Feature Selection Method in Software Defect Prediction

AO Balogun, S Basri, S Mahamad… - Computational …, 2021 - Wiley Online Library
The high dimensionality of software metric features has long been noted as a data quality
problem that affects the performance of software defect prediction (SDP) models. This …

Cascade generalization based functional tree for website phishing detection

AO Balogun, KS Adewole, AO Bajeh… - Advances in Cyber …, 2021 - Springer
The advent of the web and internet space has seen its adoption for rendering various
services-from financial to medical services. This has brought an increase in the rate of …

African buffalo optimized multinomial softmax regression based convolutional deep neural network for software fault prediction

P Saravanan, V Sangeetha - Materials Today: Proceedings, 2022 - Elsevier
Software fault prediction is an essential part of the software quality assurance to detect faulty
software modules depending on software measurement data. This models area of the …

FEDRak: Federated Learning-Based Symmetric Code Statement Ranking Model for Software Fault Forecasting

A Alhumam - Symmetry, 2023 - mdpi.com
Software Fault Forecasting (SFF) pertains to timely identifying sections in software projects
that are prone to faults and may result in significant development expenses. Deep learning …

A Hierarchical Ensemble Learning Approach for Cable Network Impairment Diagnosis

R Cassandro, JW Rupe, ZS Li - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Due to the extensive interconnectedness of components in modern engineering systems,
fault diagnosis plays a pivotal role in ensuring system reliability, operational continuity, and …

[HTML][HTML] Hybrid Bio-Optimized Algorithms for Hyperparameter Tuning in Machine Learning Models: A Software Defect Prediction Case Study

M Das, BR Mohan, RMR Guddeti, N Prasad - Mathematics, 2024 - mdpi.com
Addressing real-time optimization problems becomes increasingly challenging as their
complexity continues to escalate over time. So bio-optimization algorithms (BoAs) come into …