Open AccessResearch on Diabetes Prediction Analysis Based on Improved ANN Algorithm
Author(s) -
Yinggui Wang,
Ben Wang,
Jiazhi Di,
Jiehao Sun,
Xiya Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2010/1/012118
Subject(s) - computer science , support vector machine , diabetes mellitus , artificial intelligence , machine learning , data mining , precision and recall , algorithm , classifier (uml) , medicine , endocrinology
Diabetes mellitus is a common chronic disease with a long phase of asymptomatic. This paper focuses on five classification algorithms in machine learning, which are MLP, SVM, KNN, DT and the improved algorithm of ANN. By adjusting appropriate parameters for mining and analysing diabetes data, classifier effect is analysed according to the performance indicators of accuracy, precision, recall, and F1-score. The suitable algorithm is researched for diabetes prediction, and provides ideas for mining and analysing other disease data from current medical industry.