Diabetes Health Indicator using Machine Learning Techniques
Presentation Type
Poster
Student
Yes
Track
Health Care Application
Abstract
Diabetes Indicator using Machine Learning Techniques
Xeng Yang and Deepak Sanjel
Dept of Math and Statistics
Minnesota State University, Mankato
Machine Learning techniques such as Decision Trees (CART), Bagging, Boosting, Random Forest, Support Vector Machines (SVM), and Naïve Bayes Methods are used to improve predictions of classification models. Case studies with customer churn will be discussed, and comparisons of the accuracy between different types of models will be made using ROC curves.
Start Date
2-6-2024 1:00 PM
End Date
2-6-2024 2:00 PM
Diabetes Health Indicator using Machine Learning Techniques
Volstorff A
Diabetes Indicator using Machine Learning Techniques
Xeng Yang and Deepak Sanjel
Dept of Math and Statistics
Minnesota State University, Mankato
Machine Learning techniques such as Decision Trees (CART), Bagging, Boosting, Random Forest, Support Vector Machines (SVM), and Naïve Bayes Methods are used to improve predictions of classification models. Case studies with customer churn will be discussed, and comparisons of the accuracy between different types of models will be made using ROC curves.