An Architecture and Domain Specific Language Framework for Repeated Domain-Specific Predictive Modeling

Harlan D. Harris
Proceedings of The 4th International Conference on Predictive Applications and APIs, PMLR 82:23-32, 2018.

Abstract

When repeatedly fitting related predictive models within the same domain, for similar problems, it’s helpful to have tools to support an efficient, high-quality workflow. This paper describes a theory of the architecture for such tools and for the interfaces among predictive models and other aspects of a software system. Additionally, it describes an open-source reference implementation of this design, written in R, focusing on a Domain Specific Language for one specific repeated predictive modeling task.

Cite this Paper

BibTeX
@InProceedings{pmlr-v82-harris18a, title = {An Architecture and Domain Specific Language Framework for Repeated Domain-Specific Predictive Modeling}, author = {Harris, Harlan D.}, booktitle = {Proceedings of The 4th International Conference on Predictive Applications and APIs}, pages = {23--32}, year = {2018}, editor = {Hardgrove, Claire and Dorard, Louis and Thompson, Keiran}, volume = {82}, series = {Proceedings of Machine Learning Research}, month = {24--25 Oct}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v82/harris18a/harris18a.pdf}, url = {https://proceedings.mlr.press/v82/harris18a.html}, abstract = {When repeatedly fitting related predictive models within the same domain, for similar problems, it’s helpful to have tools to support an efficient, high-quality workflow. This paper describes a theory of the architecture for such tools and for the interfaces among predictive models and other aspects of a software system. Additionally, it describes an open-source reference implementation of this design, written in R, focusing on a Domain Specific Language for one specific repeated predictive modeling task.} }
Endnote
%0 Conference Paper %T An Architecture and Domain Specific Language Framework for Repeated Domain-Specific Predictive Modeling %A Harlan D. Harris %B Proceedings of The 4th International Conference on Predictive Applications and APIs %C Proceedings of Machine Learning Research %D 2018 %E Claire Hardgrove %E Louis Dorard %E Keiran Thompson %F pmlr-v82-harris18a %I PMLR %P 23--32 %U https://proceedings.mlr.press/v82/harris18a.html %V 82 %X When repeatedly fitting related predictive models within the same domain, for similar problems, it’s helpful to have tools to support an efficient, high-quality workflow. This paper describes a theory of the architecture for such tools and for the interfaces among predictive models and other aspects of a software system. Additionally, it describes an open-source reference implementation of this design, written in R, focusing on a Domain Specific Language for one specific repeated predictive modeling task.
APA
Harris, H.D.. (2018). An Architecture and Domain Specific Language Framework for Repeated Domain-Specific Predictive Modeling. Proceedings of The 4th International Conference on Predictive Applications and APIs, in Proceedings of Machine Learning Research 82:23-32 Available from https://proceedings.mlr.press/v82/harris18a.html.

Related Material