Reviewing ensemble classification methods in breast cancer

M Hosni, I Abnane, A Idri, JMC de Gea… - Computer methods and …, 2019‏ - Elsevier
Context Ensemble methods consist of combining more than one single technique to solve
the same task. This approach was designed to overcome the weaknesses of single …

Data preprocessing for heart disease classification: A systematic literature review

H Benhar, A Idri, JL Fernández-Alemán - Computer Methods and Programs …, 2020‏ - Elsevier
Context Early detection of heart disease is an important challenge since 17.3 million people
yearly lose their lives due to heart diseases. Besides, any error in diagnosis of cardiac …

Software effort estimation accuracy prediction of machine learning techniques: A systematic performance evaluation

Y Mahmood, N Kama, A Azmi… - Software: Practice and …, 2022‏ - Wiley Online Library
Software effort estimation accuracy is a key factor in effective planning, controlling, and
delivering a successful software project within budget and schedule. The overestimation and …

Exploring data mining and machine learning in gynecologic oncology

F Idlahcen, A Idri, E Goceri - Artificial Intelligence Review, 2024‏ - Springer
Gynecologic (GYN) malignancies are gaining new and much-needed attention, perpetually
fueling literature. Intra-/inter-tumor heterogeneity and “frightened” global distribution by race …

Software effort estimation modeling and fully connected artificial neural network optimization using soft computing techniques

S Kassaymeh, M Alweshah, MA Al-Betar… - Cluster …, 2024‏ - Springer
In software engineering, the planning and budgeting stages of a software project are of great
importance to all stakeholders, including project managers as well as clients. The estimated …

Machine learning for software engineering: A tertiary study

Z Kotti, R Galanopoulou, D Spinellis - ACM Computing Surveys, 2023‏ - dl.acm.org
Machine learning (ML) techniques increase the effectiveness of software engineering (SE)
lifecycle activities. We systematically collected, quality-assessed, summarized, and …

Heterogeneous ensemble model to optimize software effort estimation accuracy

SS Ali, J Ren, K Zhang, J Wu, C Liu - IEEE Access, 2023‏ - ieeexplore.ieee.org
The software industry has experienced rapid expansion in recent years, with software
development now essential to the success of many multinational corporations. The demand …

Data-driven effort estimation techniques of agile user stories: a systematic literature review

B Alsaadi, K Saeedi - Artificial Intelligence Review, 2022‏ - Springer
At an early stage in the development process, a development team must obtain insight into
the software being developed to establish a reliable plan. Thus, the team members should …

Research patterns and trends in software effort estimation

SK Sehra, YS Brar, N Kaur, SS Sehra - Information and Software …, 2017‏ - Elsevier
Context Software effort estimation (SEE) is most crucial activity in the field of software
engineering. Vast research has been conducted in SEE resulting into a tremendous …

Investigating the use of random forest in software effort estimation

H Mustapha, N Abdelwahed - Procedia computer science, 2019‏ - Elsevier
Over the last two decades, there has been an important increase in studies dealing with the
software development effort estimation (SDEE) using machine learning (ML) techniques that …