Publication Type
Book Chapter
Version
publishedVersion
Publication Date
4-2018
Abstract
This chapter provides an introduction on feature generation and engineering for software analytics. Specifically, we show how domain-specifc features can be designed and used to automate three software engineering tasks: (1) detecting defective software modules (defect prediction), (2) identifying crashing mobile app release (crash release prediction), and (3) predicting who will leave a software team (developer turnover prediction). For each of the three tasks, different sets of features are extracted from a diverse set of software artifacts, and used to build predictive models.
Discipline
Numerical Analysis and Scientific Computing | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Feature engineering for machine learning and data analytics
Editor
Guozhu Dong, and Huan Liu
First Page
335
Last Page
358
ISBN
9781138744387
Identifier
10.1201/9781315181080-13
Publisher
CRC Press
City or Country
Boca Raton, FL
Citation
XIA, Xin and LO, David.
Feature Engineering for Machine Learning and Data Analytics. (2018). Feature engineering for machine learning and data analytics. 335-358.
Available at: https://ink.library.smu.edu.sg/sis_research/4362
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1201/9781315181080-13