Framework for Alzheimer Diseases Classification using Machine Learning Algorithms

Abstract

At Least 50 million people in the world are assumed to have Alzheimer Disease (AD). Hence early diagnosis as well as early dose of memantine is required to inhibit further increase of this disease. In this paper a framework is proposed for classification of Alzheimer using five different Machine Learning models. Dataset is taken from Kaggle website after that Data preprocessing takes place. Five different models viz. Logistic Regression, Support Vector Machine, Random Forest, Decision Tree and Gradient Boosting Classifier are compared using various evaluation metrics such as Accuracy, Precision, Recall, Log loss and AUC-ROC.