TopicScore: The Topic SCORE Algorithm to Fit Topic Models
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>.
| Version: |
0.0.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
utils, stats, graphics, RSpectra, combinat, quadprog, methods, Matrix, slam |
| Published: |
2019-06-06 |
| Author: |
Minzhe Wang [aut, cre],
Tracy Ke [aut] |
| Maintainer: |
Minzhe Wang <minzhew at uchicago.edu> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| CRAN checks: |
TopicScore results |
Documentation:
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