M.Tech Statistics, Federal university of Technology, Akure (2023).
B.Sc. Statistics, University of Ilorin (2019).
The topic of the research is “feature selection and classification of diabetes types using machine learning models”.The main aim of the study is to develop machine learning based prediction models for diabetic patients and to identify which machine learning algorithm has the ability to accurately and precisely classify diabetes types. Machine learning techniques was applied to classify diabetes types into “Type 1” or “Type 2” using a secondary dataset collected from Federal Medical Centre, Abeokuta. The results showed that Linear Discriminant Analysis (LDA) was the best-performing algorithm followed by Bayesian Generalized Linear Model. While the most important variables are ‘Age’, ‘Plasma Glucose’, ‘Diastolic BP’, ‘Height’, ‘Weight’, ‘BMI’ and ‘Diabetic pedigree’. Conclusions from the research showed that machine learning algorithms can be used to make an early diagnosis of diabetes.
1. Statistics for Agricultural and Biological Sciences(STA 201). Introduction to Statistics(PHE 201). Introduction to Biostatistics( ITH 203/PHE 205)
2. No administrative role
Non member
