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This paper presents a fraud detection system for wireless communication using an enhanced machine learning algorithm called XGBoost, which is based on Gradient-boosted Decision Trees. The methodology involves data preprocessing techniques like SMOTE for class balancing and Auto encoders for dimensionality reduction, achieving high precision and recall rates of 99.2% and 99%, respectively. The proposed method outperforms existing techniques in terms of accuracy and efficiency in detecting fraudulent transact

Author
vempallyrakeshimatiz
Language
EN