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eXtreme gradient boosting algorithm with machine learning: A review
< jats: p> The primary task of machine learning is to extract valuable information from the
data that is generated every day, process it to learn from it, and take useful actions. Original …
data that is generated every day, process it to learn from it, and take useful actions. Original …
[HTML][HTML] Ai in thyroid cancer diagnosis: Techniques, trends, and future directions
Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years,
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
offering advanced tools and methodologies that promise to revolutionize patient outcomes …
Forecasting gold price with the XGBoost algorithm and SHAP interaction values
Financial institutions, investors, mining companies and related firms need an effective
accurate forecasting model to examine gold price fluctuations in order to make correct …
accurate forecasting model to examine gold price fluctuations in order to make correct …
Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process
The stock market has performed one of the most important functions in a laissez-faire
economic system by gathering people, companies, and flows of money for several centuries …
economic system by gathering people, companies, and flows of money for several centuries …
A survey on multi-objective hyperparameter optimization algorithms for machine learning
Hyperparameter optimization (HPO) is a necessary step to ensure the best possible
performance of Machine Learning (ML) algorithms. Several methods have been developed …
performance of Machine Learning (ML) algorithms. Several methods have been developed …
Advanced hyperparameter optimization for improved spatial prediction of shallow landslides using extreme gradient boosting (XGBoost)
Abstract Machine learning algorithms have progressively become a part of landslide
susceptibility map** practices owing to their robustness in dealing with complicated and …
susceptibility map** practices owing to their robustness in dealing with complicated and …
[HTML][HTML] A survey on wearable technology: History, state-of-the-art and current challenges
Technology is continually undergoing a constituent development caused by the appearance
of billions new interconnected “things” and their entrenchment in our daily lives. One of the …
of billions new interconnected “things” and their entrenchment in our daily lives. One of the …
Interpretable machine learning for predicting the strength of 3D printed fiber-reinforced concrete (3DP-FRC)
This study aims to provide an effective and accurate machine learning approach to predict
the compressive strength (CS) and flexural strength (FS) of 3D printed fiber reinforced …
the compressive strength (CS) and flexural strength (FS) of 3D printed fiber reinforced …
The comparison of LightGBM and XGBoost coupling factor analysis and prediagnosis of acute liver failure
D Zhang, Y Gong - Ieee Access, 2020 - ieeexplore.ieee.org
This paper focuses on the comparison of dimensionality reduction effect between LightGBM
and XGBoost-FA. With respect to XGBoost, LightGBM can be built in the effect of …
and XGBoost-FA. With respect to XGBoost, LightGBM can be built in the effect of …
Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
Hybrid artificial intelligence (AI) models are developed for sediment lead (Pb) prediction in
two Bays (ie, Bramble (BB) and Deception (DB)) stations, Australia. A feature selection (FS) …
two Bays (ie, Bramble (BB) and Deception (DB)) stations, Australia. A feature selection (FS) …