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Imbalanced data is an important issues and challenges faced in data classification. This will lead to poor performance of binary classifiers, this is due to bias in classification in favour of the majority class and lack...

Nutritional status of toddlers was considered a key indicator for assessing nutritional problems among children. According to the Banyuwangi Regency Health Profile, the prevalence of undernutrition based on the weight-fo...

One such serious problem in machine learning (ML) is imbalanced datasets. Minority class samples are usually sparse but hold significant meaning. The model can become biased toward the majority class due to unbalanced cl...

Abstract In many real-world applications, binary and multi-class classification problems involving imbalanced data and overlapping boundaries present a significant challenge for traditional machine learning algorithms. I...

In the era of emerging technologies, the transportation system is witnessing the introduction of innovative mobility services, such as autonomous vehicles, which possess unique service features that cannot be seen from c...

Context. The creation of a 3D map of the bulge using RR Lyrae (RRL) is one of the main goals of the VISTA Variables in the Via Lactea Survey (VVV) and VVV(X) surveys. The overwhelming number of sources undergoing analysi...

In recent years, the frequency and complexity of financial fraud have been rising and have become an urgent challenge for the global financial system. Traditional rule-based detection methods struggle to cope with new ty...

Imbalance of data between classes can result in incorrect predictions in classification, which can cause problems in decision making. Eastern Indonesia (KTI) is one of the regions that has a Human Development Index (HDI)...

In many critical real world classification problems one of the classes has much less samples than the others (class imbalance). In a previous work we introduced the REPMAC algorithm to solve imbalanced problems. Using a ...

With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding ...