Support vector machine - Wikipedia
In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised max-margin models with associated learning algorithms that analyze data for …
Support Vector Machine (SVM) Algorithm - GeeksforGeeks
Nov 13, 2025 · The key idea behind the SVM algorithm is to find the hyperplane that best separates two classes by maximizing the margin between them. This margin is the distance …
1.4. Support Vector Machines — scikit-learn 1.8.0 documentation
When training an SVM with the Radial Basis Function (RBF) kernel, two parameters must be considered: C and gamma. The parameter C, common to all SVM kernels, trades off …
What Is Support Vector Machine? | IBM
A support vector machine (SVM) is a supervised machine learning algorithm that classifies data by finding an optimal line or hyperplane that maximizes the distance between each class in an …
Support Vector Machine (SVM) Explained: Components & Types
Support vector machines (SVMs) are algorithms used to help supervised machine learning models separate different categories of data by establishing clear boundaries between them. …
What is a support vector machine (SVM)? - TechTarget
Nov 25, 2024 · A support vector machine (SVM) is a type of supervised learning algorithm used in machine learning to solve classification and regression tasks. SVMs are particularly good at …
Support Vector Machine (SVM) Algorithm - Great Learning
Mar 18, 2025 · Support Vector Machine (SVM) is a supervised machine learning algorithm used for classification and regression tasks. It is widely applied in fields like image recognition, text …