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CatBoost for big data: an interdisciplinary review [PDF]
Journal of Big Data, 2020 Gradient Boosted Decision Trees (GBDT’s) are a powerful tool for classification and regression tasks in Big Data. Researchers should be familiar with the strengths and weaknesses of current implementations of GBDT’s in order to use them effectively and ...
John T. Hancock, Taghi M. Khoshgoftaar
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CatBoost Optimization Using Recursive Feature Elimination
JOIN: Jurnal Online InformatikaCatBoost is a powerful machine learning algorithm capable of classification and regression application. There are many studies focusing on its application but are still lacking on how to enhance its performance, especially when using RFE as a feature ...
Agus Hadianto, Wiranto Herry Utomo
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Geocarto International, 2023 Estimation of carbon stock in seagrass meadows is in challenges of paucity of assessment and low accuracy of the estimates. In this study, we used a fusion of the synthetic aperture radar (SAR) Sentinel-1 (S-1), the multi-spectral Sentinel-2 (S-2), and ...
Nam-Thang Ha +4 more
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Anticancer drug synergy prediction based on CatBoost
PeerJ Computer Science, 2023 Background The research of cancer treatments has always been a hot topic in the medical field. Multi-targeted combination drugs have been considered as an ideal option for cancer treatment. Since it is not feasible to use clinical experience or high-throughput screening to identify the complete combinatorial space, methods such as machine learning ...
Changheng Li, Nana Guan, Hongyi Zhang
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Fire Prediction Based on CatBoost Algorithm [PDF]
Mathematical Problems in Engineering, 2021 In recent years, increasingly severe wildfires have posed a significant threat to the safe and stable operation of transmission lines. Wildfire risk assessment and early warning have become an important research topic in power grid risk assessment. This study proposes a fire prediction model on the basis of the CatBoost algorithm to effectively predict
Fangrong Zhou +6 more
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CAT-RFE: ensemble detection framework for click fraud
网络与信息安全学报, 2022 Click fraud is one of the most common methods of cybercrime in recent years, and the Internet advertising industry suffers huge losses every year because of click fraud.In order to effectively detect fraudulent clicks within massive clicks, a variety of ...
Yixiang LU, Guanggang GENG, Zhiwei YAN, Xiaomin ZHU, Xinchang ZHANG
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Applied Sciences, 2023 In light of the escalating ubiquity of the Internet, the proliferation of cyber-attacks, coupled with their intricate and surreptitious nature, has significantly imperiled network security.
Yujie Zhang, Zebin Wang
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GIScience & Remote Sensing, 2021 Quantifying total carbon (TC) stocks in soil across various mangrove ecosystems is key to understanding the global carbon cycle to reduce greenhouse gas emissions. Estimating mangrove TC at a large scale remains challenging due to the difficulty and high
Tien Dat Pham +7 more
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IoT Botnet Attack Detection Model Based on DBO-Catboost
Applied Sciences, 2023 With the widespread adoption of Internet of Things (IoT) technology, the increasing number of IoT devices has led to a rise in serious network security issues. Botnets, a major threat in network security, have garnered significant attention over the past
Changjin Yang, Weili Guan, Zhijie Fang
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Barekeng, 2022 Diabetes mellitus as a metabolic disease characterized by hyperglycemia can be dangerous if it cannot be handled properly. Early detection of existing symptoms can reduce the impact of delays in treatment.
Novia Permatasari +3 more
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