Matrix decomposition algorithms.
These include PCA, NMF, ICA, and more. Most of the algorithms of this module can be regarded as dimensionality reduction techniques.
Dictionary learning.
Factor Analysis (FA).
FastICA: a fast algorithm for Independent Component Analysis.
Incremental principal components analysis (IPCA).
Kernel Principal component analysis (KPCA).
Latent Dirichlet Allocation with online variational Bayes algorithm.
Mini-batch dictionary learning.
Mini-Batch Non-Negative Matrix Factorization (NMF).
Mini-batch Sparse Principal Components Analysis.
Non-Negative Matrix Factorization (NMF).
Principal component analysis (PCA).
Sparse coding.
Sparse Principal Components Analysis (SparsePCA).
Dimensionality reduction using truncated SVD (aka LSA).
Solve a dictionary learning matrix factorization problem.
Solve a dictionary learning matrix factorization problem online.
Perform Fast Independent Component Analysis.
Compute Non-negative Matrix Factorization (NMF).
Sparse coding.
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