The integration of complex systems approaches with statistical modeling, machine learning, and artificial intelligence (AI) opens new frontiers for understanding these complexities and improving ...

Budoen, A.T., Zhang, M.W. and Edwards Jr., L.Z. (2025) A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites. Open Access Library Journal, 12, ...

A proteomics-driven 24-protein classifier improves the differentiation of thyroid adenoma and carcinoma, retrospectively and ...

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Finally, based on the weighted data, Spearman correlation analysis was used to quantitatively evaluate the association strength of each variable with heart failure classification, and the core ...

Systems controlled by next-generation computing algorithms ... tasks than its linear counterpart and is significantly less computationally complex than a previous machine learning-based controller.

Linear regression algorithms fit a straight line ... categories of problems that are often solved by machine learning: regression and classification. Regression is for numeric data (e.g. What ...

Machine learning algorithms are the engines of ... Logistic regression is a method for solving categorical classification problems that uses linear regression inside a sigmoid or logit function ...