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There are many applications available for detecting the electricity theft. However, only few studies compare the machine learning techniques in discovering electricity-stealing behavior. This study, therefore, compares the predictive accuracy of several machine learning methods including Logistic Regression (LR), The K-Nearest Neighbor Algorithm, (K-NN), Support Vector Machines (SVM), and Neural Networks (NNet) for predicting the electricity thefts in a concrete model.
Gu et al. (Mon,) studied this question.