In this paper, a novel hybrid approach integrating genetic algorithm (GA) and support vector machines (SVM) is proposed to conduct the key factor exploration tasks in the core competitiveness ...

Support vector machines (SVM): SVM is a powerful classification and regression algorithm that performs well in dealing with non-linear relationships.

He’s credited with coming up with the first support vector machine (SVM) algorithm. SVMs are widely used today for machine learning purposes.

Other common machine learning regression algorithms (short of neural networks) include Naive Bayes, Decision Tree, K-Nearest Neighbors, LVQ (Learning Vector Quantization), LARS Lasso, Elastic Net ...

EHR data may be particularly suitable for machine learning (ML) techniques, as such algorithms can process high-dimensional data and capture nonlinear relationships between variables. By comparison, ...

The BO-GBRT model accurately predicts compressive strength in self-compacting concrete with recycled aggregates, improving upon traditional testing methods.

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams ...