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What is Area Under the Curve (AUC) Score

Chapter 8
Handbook of Research on Applications and Implementations of Machine Learning Techniques
Area under the curve (AUC) is a binary classification metric. It considers all the possible thresholds. Different threshold values result in distinct true positive/false positive rates. As the threshold is decreased, more true positives (but also more false positives) instances are discovered.
Published in Chapter:
Machine Learning in Python: Diabetes Prediction Using Machine Learning
Astha Baranwal (VIT University, India), Bhagyashree R. Bagwe (VIT University, India), and Vanitha M (VIT University, India)
Copyright: © 2020 |Pages: 27
DOI: 10.4018/978-1-5225-9902-9.ch008
Abstract
Diabetes is a disease of the modern world. The modern lifestyle has led to unhealthy eating habits causing type 2 diabetes. Machine learning has gained a lot of popularity in the recent days. It has applications in various fields and has proven to be increasingly effective in the medical field. The purpose of this chapter is to predict the diabetes outcome of a person based on other factors or attributes. Various machine learning algorithms like logistic regression (LR), tuned and not tuned random forest (RF), and multilayer perceptron (MLP) have been used as classifiers for diabetes prediction. This chapter also presents a comparative study of these algorithms based on various performance metrics like accuracy, sensitivity, specificity, and F1 score.
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