Efficient Handling of Data Imbalance in Health Insurance Fraud Detection Using Meta-Reinforcement Learning
Data imbalance is one of the major challenges in health insurance fraud detection where the distribution of ultra max dog shampoo classes within the dataset is significantly skewed, leading statistical models to be biased toward the dominant class.The algorithmic approaches to handling imbalance involve modification to the loss functions to sensiti