I am a Econ and Data Analytics grad from Michigan State University. My interests lie in Predictive Modeling and Data Analysis in solving problems in Healthcare. Specificially, I am interested in Algorithms and their role in predicting health outcomes.

My work

My work is on predictive modeling for disease detection. Specifically, I developed two classifiers using logistic regression and gradient boost to predict diabetes. My goal was to determine the better classifier by comparing their metrics: accuracy, sensitivity, specificity, and ROC-AUC. In this context, the best classifier was selected based on accuracy and sensitivity, also known as the true positive rate. This project taught me the importance of error reduction and model selection in classification.