📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

The impact of parameter tuning on software effort estimation using learning machines (2013)

First Author: Song L

Attributed to: DAASE: Dynamic Adaptive Automated Software Engineering funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1145/2499393.2499394

Publication URI: http://dx.doi.org/10.1145/2499393.2499394

Type: Conference/Paper/Proceeding/Abstract