A machine learning study evaluating UCI breast tumor data demonstrated that the XGBoost model achieved 97.3 percent accuracy, ...
Scientists have developed a new AI model that could provide UN nuclear inspectors with advanced capabilities to ...
Urban flooding increasingly disrupts transport systems in rapidly urbanizing cities, yet road-oriented flood-susceptibility assessments that integrate recurrent flood observations with geographically ...
A clearer view of coming prices could make those decisions less uncertain, especially when weather problems and market ...
A research team comprising Md Samdani Azad, Minji Choi, and Tae-Hyung Lee has developed an explainable multi-target machine learning framework based on ...
Low-strain pile integrity testing (LSPIT) is widely used for rapid pile screening, but reflectogram interpretation remains difficult because defect morphology, axial extent, signed relative ...
A new hybrid quantum network flags suspicious accounts with fewer false alarms, improving trade surveillance analytics.
Machine learning project for diamond price prediction using XGBoost, regression model comparison, and a Python Tkinter interface. - bernayaman03/Diamond-Price-Prediction ...
As diversity in work styles expands in society, more people are considering side hustles as data analysis professionals to ...
H2O.ai today announced H2O-3 Secure, a commercially licensed, production-grade edition of its open source machine learning platform, H2O-3. Available immediately, H2O-3 Secure gives enterprises in ...
Air pollution monitoring is essential for understanding environmental conditions and assessing potential health risks. This project implements a machine learning-based approach to predict PM2.5 ...
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