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2021 | OriginalPaper | Chapter
Binary Prediction
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Abstract
Binary prediction is one of the most widely used analytical techniques having many applications in multiple domains. In the business context, it is used to predict loan default, discontinuance of insurance policies, customer attrition, fraud detection, etc. Because of its huge importance, a number of methods have been developed to solve this problem. In this article, we discuss the well-known logistic regression predictor and compare its performance with a relatively less widely used predictor—the maximum score predictor—using two real-life unbalanced datasets. The maximum score predictor is observed to perform better than the logistic regression predictor for both these unbalanced datasets, indicating that the maximum score predictor can be a useful addition to the analysts toolkit when dealing with the binary prediction problem.