This research aims to reactivate object-oriented databases using intelligent tools to improve performance and accuracy in ...

In a sport where tactics, terrain, weather, and timing all merge into one fluid contest, predicting the outcome of a cycling race can seem like guesswork.

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Discover the ultimate roadmap to mastering machine learning skills in 2025. Learn Python, deep learning, and more to boost ...

Urban vegetation classification is challenging due to the heterogeneous nature of urban environments. Accurate mapping of urban vegetation, which plays a crucial role in regulating microclimates, ...

Fiber-optic ATR-IR spectroscopy enables real-time liver tumor classification during surgery, offering faster and more objective diagnostics with machine learning support.

Q&A Predicting the Future Using Azure Machine Learning By David Ramel 05/13/2025 The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach ...

Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...

Supervised classification uses random forest (RF), support vector machine (SVM), classification and regression trees (CARTs), gradient boosting trees (GBTs), and naïve Bayes. An accuracy assessment ...

This article presents a predictive model using supervised machine learning, highlighting the importance of advanced optimization algorithms. Our approach focuses on a nonsmooth loss function known for ...

This research employs seven supervised machine learning classification algorithms and follows a comprehensive methodology that includes data balancing and hyperparameter tuning. To explain the ...