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Contents
4. Unsupervised learning
4. Unsupervised learning
ΒΆ
4.1. Gaussian mixture models
4.1.1. GMM classifier
4.2. Clustering
4.2.1. Affinity propagation
4.2.2. Mean Shift
4.2.3. K-means
4.2.4. Spectral clustering
4.3. Decomposing signals in components (matrix factorization problems)
4.3.1. Principal component analysis (PCA)
4.3.2. Independent component analysis (ICA)