Support Vector Machines
Data Science · University of Applied Sciences · Machine Learning
This unit introduces the concepts of Support Vector Machines (SVMs), including kernel functions and SVM formulation. Students will learn how to apply SVMs for both classification and regression tasks.
Zum Üben gibt es 50 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Introduction to Support Vector Machines
- Kernel Functions
- SVM Formulation for Classification
- SVM Formulation for Regression
- Applications of SVMs in Classification and Regression
- Advantages and Disadvantages of SVMs
Stichworte
- SVM
- Classification
- Regression
- Hyperplane
- Support Vectors
- Margin