| Name : R-TopicScore
| |
| Version : 0.0.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.3.7
| Date : 2024-06-14 11:41:54
|
| Group : Development/Libraries/Other
| Source RPM : R-TopicScore-0.0.1-lp153.3.7.src.rpm
|
| Size : 0.74 MB
| |
| Packager : (none)
| |
| Summary : The Topic SCORE Algorithm to Fit Topic Models
|
Description :
Provides implementation of the \"Topic SCORE\" algorithm that is proposed
by Tracy Ke and Minzhe Wang. The singular value decomposition step is
optimized through the usage of svds() function in \'RSpectra\' package,
on a \'dgRMatrix\' sparse matrix. Also provides a column-wise error
measure in the word-topic matrix A, and an algorithm for recovering the
topic-document matrix W given A and D based on quadratic programming.
The details about the techniques are explained in the paper \"A new SVD
approach to optimal topic estimation\" by Tracy Ke and Minzhe Wang
(2017) < arXiv:1704.07016>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
