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Support Vector Data Description (SVDD)

MATLAB Code for abnormal detection using SVDD

Version 2.2, 13-MAY-2022

Email: [email protected]

✨ MAIN FEATURES

• SVDD model for one-class or binary classification
• Multiple kinds of kernel functions (linear, gaussian, polynomial, sigmoid, laplacian)
• Visualization of decision boundaries for 2D or 3D data
• Parameter optimization using Bayesian optimization, genetic algorithm, and pParticle swarm optimization
• Weighted SVDD model
• Hybrid-kernel SVDD model (K =w1×K1+w2×K2+...+wn×Kn)

⚠️ NOTICES

• This version of this code is not compatible with the versions lower than R2016b.
• The label must be 1 for positive sample or -1 for negative sample.
• Detailed applications please see the provided demonstrations.
• This code is for reference only.