Classification problems of unbalanced data sets are commonplace in industrial production
and medical research fields. Different approaches have been proposed to handle these …

Soft computing models based on fuzzy or probabilistic approaches provide decision system
makers with the necessary capabilities to deal with imprecise and incomplete information …

Imbalanced class distributions in machine learning, where the minority class is often under-
represented, pose a substantial challenge. Synthetic Minority Over-sampling Technique …

The Synthetic Minority Over-Sampling Technique (SMOTE) is one of the most well-known
methods to solve the unequal class distribution problem in imbalanced datasets. However, it …

The dietary recommendations for individuals with diabetes focus on maintaining a balanced
nutritional intake to manage blood sugar levels. This study suggests a nutritional strategy to …

Аннотация Diabetes is a dangerous disease that increases in incidence every year. The
aim of this paper is to present and analyze the model of diabetes and its complications with …

The major problem facing users of Hopfield neural networks is the automatic choice of
hyperparameters depending on the optimisation problem. This work introduces an automatic …

Diabetes is becoming more and more dangerous, and the effects continue to grow due to
the population's ignorance of the seriousness of this phenomenon. The studies that have …

In the realm of Big Data analysis, the pivotal question of data clustering takes center stage.
This study delves into optimizing this analysis by adopting a hybrid approach that integrates …

Diabetes is a chronic disease that affects millions of people worldwide. In this work, we
propose a confident version of the density-based support vector machine for early detection …