Rare events, especially those that could potentially negatively impact society, often require
humans' decision-making responses. Detecting rare events can be viewed as a prediction …

Imbalance in dataset enforces numerous challenges to implement data analytic in all
existing real world applications using machine learning. Data imbalance occurs when …

Nowadays, in the international scientific community of machine learning, there exists an
enormous discussion about the use of black-box models or explainable models; especially …

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

Financial threats are displaying a trend about the credit risk of commercial banks as the
incredible improvement in the financial industry has arisen. In this way, one of the biggest …

Customer credit scoring is a dynamic interactive process. Simply designing the static reward
function for deep reinforcement learning may be difficult to guide an agent to adapt to the …

Most of the classification methods assume that the numbers of class observations are
balanced. In such cases, models are predicted by giving biased weight to the the class with …

Heart diseases are highly ranked among the leading causes of mortality in the world. They
have various types including vascular, ischemic, and hypertensive heart disease. A large …

Numerous imbalanced datasets exist in modern machine learning dilemmas. Challenges of
generalization and fairness stem from the existence of underrepresented classes with …

Personality refer to the distinctive set of characteristics of a person that effect their habits,
behaviour's, attitude and pattern of thoughts. Text available on Social Networking sites …