mlpack
3.0.2

mlpack::svd Namespace Reference
Classes  
class  QUIC_SVD 
QUICSVD is a matrix factorization technique, which operates in a subspace such that A's approximation in that subspace has minimum error(A being the data matrix). More...  
class  RandomizedBlockKrylovSVD 
Randomized block krylov SVD is a matrix factorization that is based on randomized matrix approximation techniques, developed in in "Randomized Block Krylov Methods for Stronger and Faster Approximate
Singular Value Decomposition". More...  
class  RandomizedSVD 
Randomized SVD is a matrix factorization that is based on randomized matrix approximation techniques, developed in in "Finding structure with randomness:
Probabilistic algorithms for constructing approximate matrix decompositions". More...  
class  RegularizedSVD 
Regularized SVD is a matrix factorization technique that seeks to reduce the error on the training set, that is on the examples for which the ratings have been provided by the users. More...  
class  RegularizedSVDFunction 
The data is stored in a matrix of type MatType, so that this class can be used with both dense and sparse matrix types. More...  
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