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Medicare Fraud Detection using CatBoost
2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), 2020In this study we investigate the performance of CatBoost in the task of identifying Medicare fraud. The Medicare claims data we use as input for CatBoost contain a number of categorical features. Some of these features, such as the procedure code and provider zip code, have thousands of possible values. One contribution we make in this study is to show
John T. Hancock, Taghi M. Khoshgoftaar
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Sales Forecasting Based on CatBoost
2020 2nd International Conference on Information Technology and Computer Application (ITCA), 2020Sales forecasting is a vital technology nowadays in the retail industry. With the help of advanced machine learning and deep learning algorithms, business owners can accurately predict the sales of thousands of products and make optimum decisions based on them. In this paper, we proposed a sales forecasting system based on CatBoosting. The algorithm is
Jingyi Ding +3 more
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Social Spammer Detection Based on PSO-CatBoost
2021With the rapid development of social networks, more and more organizations or individuals use social media to communicate with each other, passing on information and getting information, etc. However, while bringing convenience to people, social media has also become the main target of malicious attackers who try to take advantage of the system ...
Shupeng Li +3 more
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CatBoost for Fraud Detection in Financial Transactions
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2021Financial fraud is an ever growing menace with severe consequences in the financial industry. Machine learning plays an active role in the fraud detection in financial transactions. However, fraud detection is still a challenging problem due to two major reasons. First, either fraudulent or non-fraudulent behaviors change fast and constantly. Secondly,
Yeming Chen, Xinyuan Han
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Link Quality Estimation Base on CatBoost
2021 13th International Conference on Communication Software and Networks (ICCSN), 2021To estimate link quality for wireless sensor networks (WSN) accurately and rapidly, an approach of link quality estimation is proposed, which is based on Category Boosting (CatBoost). Received signal strength indicator mean, link quality indicator mean and the signal to noise ratio mean are selected as the link quality parameters.
Tingzhong Xiao, Linlan Liu, Jian Shu
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Performance of CatBoost and XGBoost in Medicare Fraud Detection
2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020Due to the size of the data involved, performance is an important consideration in the task of detecting fraudulent Medicare insurance claims. We evaluate CatBoost and XGBoost on the task of Medicare fraud detection, and report performance in terms of running time and Area Under the Receiver Operating Characteristic Curve (AUC).
John T. Hancock, Taghi M. Khoshgoftaar
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Shortest Path Distance Prediction Based on CatBoost
2021Shortest path distances between node pairs on road networks are essential for many applications. Traditional methods, such as breadth first search (BFS) and Dijkstra algorithm, focus on precise result. However, they are difficult to apply to the large-scale road network because of the high time cost.
Liying Jiang +5 more
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CatBoost for Nonintermittent Demand in the Aviation Aftermarket
International Journal of Reliability, Quality and Safety EngineeringThe demand for aircraft parts is often difficult to forecast, leading to challenges in maintenance planning, inventory management, and overall operational efficiency. In this invited paper, we examine monthly demand forecasting for used aircraft parts in the nonintermittent domain (Smooth and Erratic), with CatBoost as the ...
Joffrey L. Leevy +2 more
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