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Detecting Music Genre Using Extreme Gradient Boosting [PDF]
Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018 This paper summarizes our contribution to the CrowdAI music genre classification challenge "Learning to Recognise Musical Genre from Audio on the Web'' as part of the WebConference 2018. We utilize different approaches from the field of music analysis to predict the music genre of given mp3 music files, including a convolutional neural network for ...
Benjamin Murauer, Günther Specht
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Boosting Privately: Federated Extreme Gradient Boosting for Mobile Crowdsensing
2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS), 2020 Recently, Google and other 24 institutions proposed a series of open challenges towards federated learning (FL), which include application expansion and homomorphic encryption (HE). The former aims to expand the applicable machine learning models of FL. The latter focuses on who holds the secret key when applying HE to FL.
Yang Liu 0118 +6 more
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Bioactive Molecule Prediction Using Extreme Gradient Boosting [PDF]
Molecules, 2016 Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today’s drug discovery process. In this paper, extreme gradient boosting (Xgboost), which is an ensemble of Classification and Regression Tree ...
Ismail Babajide Mustapha, Faisal Saeed
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Rainfall prediction using Extreme Gradient Boosting
Journal of Physics: Conference Series, 2021 Abstract Rainfall greatly affects human life in various sectors including agriculture, transportation, etc. and also can affect natural disasters such as drought, floods, and landslides. This situation prompts us to build an accurate rainfall prediction model so that prescriptive measures can be made.
M T Anwar +3 more
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Frontiers in Earth Science, 2021 Landslides are widely distributed worldwide and often result in tremendous casualties and economic losses, especially in the Loess Plateau of China.
Shibao Wang +5 more
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QUIC Network Traffic Classification Using Ensemble Machine Learning Techniques
Applied Sciences, 2023 The Quick UDP Internet Connections (QUIC) protocol provides advantages over traditional TCP, but its encryption functionality reduces the visibility for operators into network traffic.
Sultan Almuhammadi +2 more
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Frontiers in Materials, 2022 It is evident that preparing materials, casting samples, curing, and testing all need time and money. The construction sector will benefit if these problems can be handled using cutting-edge techniques like machine learning. Also, a material’s ultrasonic
Kaffayatullah Khan +5 more
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Applied Sciences, 2022 Organizations engaged in business, regardless of the industry in which they operate, must be able to extract knowledge from the data available to them. Often the volume of customer and supplier data is so large, the use of advanced data mining algorithms
Antonio Panarese +3 more
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Scientific Reports, 2022 Accurate identification of drug-targets in human body has great significance for designing novel drugs. Compared with traditional experimental methods, prediction of drug-targets via machine learning algorithms has enhanced the attention of many ...
Rahu Sikander, Ali Ghulam, Farman Ali
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A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and Prospects
IEEE Access, 2022 Ensemble learning techniques have achieved state-of-the-art performance in diverse machine learning applications by combining the predictions from two or more base models.
Ibomoiye Domor Mienye, Yanxia Sun
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