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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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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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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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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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This chapter delves into the Catboost algorithm, a machine learning method renowned for its handling of categorical data through gradient boosting techniques. It provides an in-depth analysis of Catboost's capabilities, contrasts it with other machine learning algorithms, and discusses its applications across various industries.
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Accuracy Assessment of CatBoost for Storm Damage
PROCEEDINGS of 20th International Symposium on Applied Informatics and Related AreasThis paper explores the use of gradient boosting to quantify the economic damage caused by storms and classify storm events as severe or mild. The study draws on a historical disaster open database. These figures confirm gradient boosting’s high accuracy in analysing extreme meteorological events for insurance.
Madiyarov Kuan, Letov Alexey
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Employee Attrition Analysis Using CatBoost
2023Md. Monir Ahammod Bin Atique +2 more
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Practical Application of the Catboost Model
Chapter 5 discusses the practical application of the Catboost model in handling big data for cryptocurrency market forecasting. It details the process of model building, from defining the problem and data collection to preprocessing, feature selection, model selection, training, evaluation, and deployment.openaire +1 more source
Automated Detection of Chagas Disease via CatBoost
Anais do XVII Congresso Brasileiro de Inteligência ComputacionalChagas disease, caused by Trypanosoma cruzi, is a neglected tropical disease that continues to pose a significant health threat in Latin America and is increasingly found in non-endemic regions due to migration. The chronic cardiac form of the disease (chronic Chagasic cardiomyopathy) often develops silently, making early detection difficult and ...
Rogério Ferreira Júnior +6 more
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