Model-based software effort estimation - A robust comparison of 14 algorithms widely used in the data science community
© 2019, ICIC International. The emergence of the data science discipline has facilitated the development of novel and advanced machine-learning algorithms for tackling tasks related to data analytics. For example, ensemble learning and deep learning have frequently achieved promising results in many...
Saved in:
Main Authors: | Passakorn Phannachitta, Kenichi Matsumoto |
---|---|
Format: | Journal |
Published: |
2019
|
Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85067567471&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/65518 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
Similar Items
-
Robust comparison of similarity measures in analogy based software effort estimation
by: Passakorn Phannachitta
Published: (2018) -
Meta Learning and Software Effort Estimation
by: Passakorn Phannachitta
Published: (2020) -
Bug or not? Bug Report classification using N-gram IDF
by: Pannavat Terdchanakul, et al.
Published: (2018) -
Bug or not? Bug Report classification using N-gram IDF
by: Pannavat Terdchanakul, et al.
Published: (2018) -
Estimating software projects’ effort, time, and cost using function point analysis and analogy-based effort estimation
by: Tuazon, John Byron D.
Published: (2018)