Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data scientists should master both supervised ...

Medical datasets often present a major challenge for machine learning models: skewness in continuous variables such as age, tumor size, and survival months. This skewness can undermine the assumptions ...

Linwei Zhai ᵃ, Jian Qin ᵇ, Lean Yu ᶜ, Hybridizing Support Vector Machines into Genetic Algorithm for Key Factor Exploration in Core Competence Evaluation of Aviation Manufacturing Enterprises, Filomat ...

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 ...