| Name : R-sparsepca
| |
| Version : 0.1.2
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.13
| Date : 2024-06-14 11:01:49
|
| Group : Development/Libraries/Other
| Source RPM : R-sparsepca-0.1.2-lp153.2.13.src.rpm
|
| Size : 0.05 MB
| |
| Packager : (none)
| |
| Summary : Sparse Principal Component Analysis (SPCA)
|
Description :
Sparse principal component analysis (SPCA) attempts to find sparse
weight vectors (loadings), i.e., a weight vector with only a few
\'active\' (nonzero) values. This approach provides better
interpretability for the principal components in high-dimensional data
settings. This is, because the principal components are formed as a
linear combination of only a few of the original variables. This
package provides efficient routines to compute SPCA. Specifically, a
variable projection solver is used to compute the sparse solution. In
addition, a fast randomized accelerated SPCA routine and a robust SPCA
routine is provided. Robust SPCA allows to capture grossly corrupted
entries in the data. The methods are discussed in detail by N. Benjamin
Erichson et al. (2018) < arXiv:1804.00341>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
