Support Vector Machine
(เครื่องจักรเวกเตอร์สนับสนุน)
Definition
Support Vector Machine (เครื่องจักรเวกเตอร์สนับสนุน) Hard Skill
Support Vector Machine (SVM) is a supervised machine learning algorithm used for classification and regression tasks by finding the optimal hyperplane that separates data points of different classes with maximum margin.
Expertise Level
Level 1
Basic
1. Understands the basic concept of SVM and how it separates data points.
2. Can identify linear separability in simple datasets.
3. Knows the difference between classification and regression SVM.
Level 2
Intermediate
1. Able to implement linear and non-linear SVM using kernel functions.
2. Understands the role of hyperparameters like C and gamma.
3. Can preprocess data for SVM and evaluate model performance.
Level 3
Advanced
1. Can optimize and tune SVM models for complex, high-dimensional datasets.
2. Understands advanced kernel methods and multi-class SVM strategies.
3. Able to interpret SVM model results for business or research decisions.
