dsBoltzmannMachines Package

Development name

dsBoltzmannMachines

Name of server-side packages

dsBoltzmannMachines

Name of client-side packages

dsBoltzmannMachinesClient

Date this information was late updated/checked

20/09/2021

Description of packages purpose

Boltzmann machines are generative neural networks which are able to learn the distribution of data that are fed as input to the network. The dsBoltzmannMachines package allows to train and use these generative models in DataSHIELD for creating synthetic data that preserve patterns of input data. Synthetic data samples are not linked to individual samples in the original data but are generated via sampling from the distribution that is captured by a Boltzmann machine model.

How to contact developer institution/team/individual

Stefan Lenz <lenz@imbi.uni-freiburg.de>, Universitätsklinikum Freiburg, Freiburg, Germany.

Latest version

v1.0.2

Type distribution licence

MIT License

Methods of obtaining package

CRAN Address

-

Web-site/ftp-site/other
-

What versions of R work with the package?

≥ 3.5

What R packages do the packages depend on?

dsBoltzmannMachines

JuliaConnectoR

dsBoltzmannMachinesClient

DSI
DSOpal
BoltzmannMachinesRPlots

Status

Version 1.0

Is the package tested?

Yes

Is the package documented?

Yes

Has the package had a disclosure audit?

No

Is the package suitable for deployment in the production environment? (Yes/No)

Yes

Does your package have features to protect the privacy of data, or does it just provide remote analysis functionality?

Individual data cannot be accessed via the interface of the package. The package provides only access to synthetic data that are generated from Boltzmann machines.

Additional Information

Lenz, S., Hess, M. & Binder, H. Deep generative models in DataSHIELD. BMC Med Res Methodol 21, 64 (2021). https://doi.org/10.1186/s12874-021-01237-6