Research   
Evolutionary computation technique combined with ensemble model for classification of diabetes
Author(s): K Satish Kumar*, G V Suryakanth and K Giridhar Machine learning (ML) was a rapidly advancing technology in the modern world. It had a wide variety of applications such as medical diagnosis, stock market trading, email spam, and malware filtering, etc., ML algorithms train the computer to learn from the past data and make predictions on the unknown samples. This research mainly focuses on the prediction of the PIMA Indian diabetes disease. The diabetes dataset was taken from the UCI machine learning repository. The research work was broken down into three stages. The AdaBoost technique was applied to all the features of the PIMA Indian Diabetes dataset. The correlation technique was applied for feature selection and the selected features were trained and tested with AdaBoost. A novel Hybrid Genetic Algorithm (HGA) was designed and developed for feature selection and the selected features were trained and tested with AdaBoost. .. Read More» DOI: 10.54931/2053-4787.29-5-1

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