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 …

Explainable artificial intelligence is an emerging research direction hel** the user or
developer of machine learning models understand why models behave the way they do …

Feature selection is an important data processing method to reduce dimension of the raw
datasets while preserving the information as much as possible. In this paper, an enhanced …

Data from many real-world applications can be high dimensional and features of such data
are usually highly redundant. Identifying informative features has become an important step …

Recently, many optimization algorithms have been applied for Feature selection (FS)
problems and show a clear outperformance in comparison with traditional FS methods …

A computer-aided diagnosis (CAD) system based on mammograms enables early breast
cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD …

Natural phenomena and mechanisms have always intrigued humans, inspiring the design of
effective solutions for real-world problems. Indeed, fascinating processes occur in nature …

There have been several empirical studies addressing breast cancer using machine
learning and soft computing techniques. Many claim that their algorithms are faster, easier …

Feature selection, which picks the optimal subset of characteristics related to the target data
by deleting unnecessary data, is one of the most important aspects of the machine learning …

Background The goal of this exploratory study was to develop and assess a prediction
model which can potentially be used as a biomarker of breast cancer, based on …