Explainable artificial intelligence (XAI) has received great interest in the recent decade, due
to its importance in critical application domains, such as self-driving cars, law, and …

Artificial intelligence (AI) emphasises the creation of intelligent machines/systems that
function like humans. AI has been applied to many real-world applications. Machine …

The algorithm of C4. 5 decision tree has the advantages of high classification accuracy, fast
calculation speed and comprehensible classification rules, so it is widely used for medical …

As data science becomes more mainstream, there will be an ever-growing demand for data
science tools that are more accessible, flexible, and scalable. In response to this demand …

Although cross-validation is a standard procedure for performance evaluation, its joint
application with oversampling remains an open question for researchers farther from the …

Under sampling is a popular technique for unbalanced datasets to reduce the skew in class
distributions. However, it is well-known that under sampling one class modifies the priors of …

Imbalanced data with a skewed class distribution are common in many real-world
applications. Deep Belief Network (DBN) is a machine learning technique that is effective in …

This paper presents a novel approach to deal with the imbalanced data set problem in
neural networks by incorporating prior probabilities into a cost-sensitive cross-entropy error …

Phishing email attack is a dominant cyber-criminal strategy for decades. Despite its
longevity, it has evolved during the COVID-19 pandemic, indicating that adversaries exploit …

Online class imbalance learning is a new learning problem that combines the challenges of
both online learning and class imbalance learning. It deals with data streams having very …