Research on Accurate Prediction Method of Epilepsy Stage Based on Gradient Boosting Algorithm

With the incidence rate of epilepsy increasing year by year, early diagnosis and accurate prediction of epilepsy have become a significant Research Interests in the medical field. This article explores a method of forecasting for the onset stage of epilepsy based on gradient boosting algorithm, aiming to improve the accurate prediction rate of epilepsy patients during the onset period. The prediction is based on a large amount of clinical data and EEG data of epilepsy patients, which have been standardized to improve model performance and accelerate model training speed. Train the preprocessed data using gradient boosting algorithm to reveal the correlation between learning features and the onset stage of epilepsy. The gradient boosting algorithm has unique flexibility and can cope with diverse data features. Through mechanisms such as fine feature selection, prevention of overfitting, and missing value processing, it achieves high accuracy and strong generalization ability, providing an elegant and powerful solution for tasks such as data mining and predictive modeling in various fields. Compared to traditional diagnostic methods, the prediction method based on gradient boosting algorithm has significantly improved accuracy, fully verifying the potential and advantages of gradient boosting algorithm in predicting the onset stage of epilepsy. This article verifies the accuracy and stability of gradient boosting algorithm in predicting the incidence of epilepsy through indicator evaluation, which can provide more accurate diagnostic basis for medical personnel, thereby improving the treatment effect and living quality of epilepsy patients.