Results 31 to 40 of about 87,026 (282)
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
doaj +1 more source
Remote Sensing, 2023 This paper proposes a gradient-based data fusion and classification approach for Synthetic Aperture Radar (SAR) and optical image. This method is used to intuitively reflect the boundaries and edges of land cover classes present in the dataset.
Achala Shakya +2 more
doaj +1 more source
Predictive Modeling of the Hot Metal Sulfur Content in a Blast Furnace Based on Machine Learning
Metals, 2023 The sulfur content of hot metal in a blast furnace is an important index that reflects the production effects and quality of the hot metal. Establishing an accurate prediction model for hot metal sulfur content can guide the production process.
Song Zhang +6 more
doaj +1 more source
Recursive Aggregation of Estimators by Mirror Descent Algorithm with Averaging [PDF]
, 2005 We consider a recursive algorithm to construct an aggregated estimator from a finite number of base decision rules in the classification problem. The estimator approximately minimizes a convex risk functional under the l1-constraint.
Juditsky, Anatoli +3 more
core +5 more sources
Residual geochemical gold grade prediction using extreme gradient boosting
Environmental Challenges, 2022 The increasing cost of exploration and decreasing recovery in mineral exploration necessitates the use of reliable and robust models for spatial gold grade prediction. In comparison, ordinary kriging (OK) is widely applied in geospatial data analysis for
Bemah Ibrahim +3 more
doaj +1 more source
Quantile Extreme Gradient Boosting for Uncertainty Quantification
, 2023 15 pages, 7 figures and 4 ...
Yin, Xiaozhe +5 more
openaire +2 more sources
Extreme Learning Machine Enhanced Gradient Boosting for Credit Scoring
Algorithms, 2022 Credit scoring is an effective tool for banks and lending companies to manage the potential credit risk of borrowers. Machine learning algorithms have made grand progress in automatic and accurate discrimination of good and bad borrowers.
Yao Zou, Changchun Gao
doaj +1 more source
Silver Price Forecasting Using Extreme Gradient Boosting (XGBoost) Method
Mathematics, 2023 This article presents a study on forecasting silver prices using the extreme gradient boosting (XGBoost) machine learning method with hyperparameter tuning.
Dylan Norbert Gono +2 more
doaj +1 more source
Credit Risk Analysis With Extreme Gradient Boosting and Adaptive Boosting Algorithm
Journal of Information System,Graphics, Hospitality and Technology, 2023 Credit Risk Analysis digunakan untuk mengenali resiko terhadap pinjaman untuk mencegah penunggakan pembayaran utang. Pemberian uji kelayakan pinjaman dapat di analisis menggunakan model klasifikasi. Untuk menghasilkan model credit risk analysis yang sesuai, penulis mengajukan Algoritma Extreme Gradient Boosting (XGBoost) dan Adaptive Boosting (AdaBoost)
Rosa Delima Mendrofa +3 more
openaire +1 more source
Stroke Prediction with Enhanced Gradient Boosting Classifier and Strategic Hyperparameter [PDF]
A stroke is a medical condition that occurs when the blood supply to the brain is interrupted. Stroke can cause damage to the brain that can potentially affect a person’s function and ability to move, speak, think, and feel normally. The effect of stroke
Aditya, Christian Sri Kusuma +3 more
core +2 more sources