# CP Decompositions

>> Tensor Toolbox >> CP Decompositions

The Tensor Toolbox provides the following CP-like decompositions:

- `cp_als` - Alternating least squares (ALS) method, the gold standard
- `cp_arls` - Alternating randomized least squares (ARLS) method, efficient for massive dense tensors
- `cp_als_lev` - ARLS with leverage scores (ARLS-Lev), efficient for massive sparse and dense tensors
- `cp_opt` - Direct optimization (OPT) method
- `cp_wopt` - Weighted direct optimization (WOPT) method for handling missing data
- `cp_apr` - Alternating Poisson regression (APR) using KL-divergence fitting function for Poisson tensor decomposition
- `gcp_opt` - Generalized CP with alternative loss functions
- `cp_sym` - Direct optimization for symmetric (SYM) decomposition
- `cp_isym` - Direct optimization for implicit (I) symmetric (SYM) decomposition
- `cp_spm` - Subspace Power Method (SPM) for symmetric tensor decomposition
- `cp_orth_als` - Orthogonalized ALS (Orth-ALS), a simple modification of the ALS algorithm to periodically "orthogonalize" the estimates of the factors