Optimizing diabetes prediction in machine learning models: Evaluating the effectiveness of a novel class imbalance technique—adaptive synthetic class balancing with class proportion filtering
The skewedness of results when predicting diabetes is mostly due to uneven distribution of data, especially in reducing detection rates of real patients. These are errors which cause delay in treatment or incorrect diagnosis. This work suggests a counter plan to this assumption, which is Adaptive Synthetic Class Balanc...