4. Unsupervised learning¶
- 4.1. Gaussian mixture models
- 4.2. Manifold learning
- 4.3. Clustering
- 4.3.1. K-means
- 4.3.2. Affinity propagation
- 4.3.3. Mean Shift
- 4.3.4. Spectral clustering
- 4.3.5. Hierarchical clustering
- 4.3.6. DBSCAN
- 4.3.7. Clustering performance evaluation
- 4.4. Decomposing signals in components (matrix factorization problems)
- 4.5. Covariance estimation
- 4.6. Novelty and Outlier Detection
- 4.7. Hidden Markov Models