Nothing
DBNMFrank: Rank Selection for Non-Negative Matrix Factorization
Given the non-negative data and its distribution, the package estimates the rank parameter for Non-negative Matrix Factorization. The method is based on hypothesis testing, using a deconvolved bootstrap distribution to assess the significance level accurately despite the large amount of optimization error. The distribution of the non-negative data can be either Normal distributed or Poisson distributed.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Yun Cai [aut, cre], Hong Gu [aut], Tobias Kenney [aut] |
| Maintainer | Yun Cai <Yun.Cai@dal.ca> |
| License | GPL (>= 3) |
| Version | 0.1.0 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the DBNMFrank package in your browser
Any scripts or data that you put into this service are public.
