sklearn.decomposition Library

An sklearn.decomposition Library is a matrix decomposition system that is an sklearn library.

• Context:
  • It can contain sklearn.decomposition.PCA, sklearn.decomposition.SVD, ...
• See: [[]].

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References

2019

• "2.5. Decomposing signals in components (matrix factorization problems)." In: scikit-learn documentation.

   2.5. Decomposing signals in components (matrix factorization problems)
       2.5.1. Principal component analysis (PCA)
           2.5.1.1. Exact PCA and probabilistic interpretation
           2.5.1.2. Incremental PCA
           2.5.1.3. PCA using randomized SVD
           2.5.1.4. Kernel PCA
           2.5.1.5. Sparse principal components analysis (SparsePCA and MiniBatchSparsePCA)
       2.5.2. Truncated singular value decomposition and latent semantic analysis
       2.5.3. Dictionary Learning
           2.5.3.1. Sparse coding with a precomputed dictionary
           2.5.3.2. Generic dictionary learning
           2.5.3.3. Mini-batch dictionary learning
       2.5.4. Factor Analysis
       2.5.5. Independent component analysis (ICA)
       2.5.6. Non-negative matrix factorization (NMF or NNMF)
           2.5.6.1. NMF with the Frobenius norm
           2.5.6.2. NMF with a beta-divergence
       2.5.7. Latent Dirichlet Allocation (LDA)

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