The impact of automated feature selection techniques on the interpretation of defect models
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
The impact of automated feature selection techniques on the interpretation of defect models
Authors
Keywords
-
Journal
EMPIRICAL SOFTWARE ENGINEERING
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-08-01
DOI
10.1007/s10664-020-09848-1
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- An Empirical Study of Model-Agnostic Techniques for Defect Prediction Models
- (2020) Jirayus Jiarpakdee et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- The Unreasonable Effectiveness of Software Analytics
- (2018) Tim Menzies IEEE SOFTWARE
- The Impact of Automated Parameter Optimization on Defect Prediction Models
- (2018) Chakkrit Tantithamthavorn et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- A Hybrid Feature Selection Method for Complex Diseases SNPs
- (2018) Raid Alzubi et al. IEEE Access
- The Use of Summation to Aggregate Software Metrics Hinders the Performance of Defect Prediction Models
- (2017) Feng Zhang et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- An Empirical Comparison of Model Validation Techniques for Defect Prediction Models
- (2017) Chakkrit Tantithamthavorn et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Comments on “Researcher Bias: The Use of Machine Learning in Software Defect Prediction”
- (2016) Chakkrit Tantithamthavorn et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Tuning for software analytics: Is it really necessary?
- (2016) Wei Fu et al. INFORMATION AND SOFTWARE TECHNOLOGY
- Feature selection and analysis on correlated gas sensor data with recursive feature elimination
- (2015) Ke Yan et al. SENSORS AND ACTUATORS B-CHEMICAL
- Researcher Bias: The Use of Machine Learning in Software Defect Prediction
- (2014) Martin Shepperd et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Data Quality: Some Comments on the NASA Software Defect Datasets
- (2013) Martin Shepperd et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Software defect prediction using Bayesian networks
- (2012) Ahmet Okutan et al. EMPIRICAL SOFTWARE ENGINEERING
- Reducing Features to Improve Code Change-Based Bug Prediction
- (2012) S. Shivaji et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- A large-scale empirical study of just-in-time quality assurance
- (2012) Yasutaka Kamei et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Evaluating defect prediction approaches: a benchmark and an extensive comparison
- (2011) Marco D’Ambros et al. EMPIRICAL SOFTWARE ENGINEERING
- Hybrid feature selection by combining filters and wrappers
- (2010) Hui-Huang Hsu et al. EXPERT SYSTEMS WITH APPLICATIONS
- Statistical Feature Selection From Massive Data in Distribution Fault Diagnosis
- (2010) Yixin Cai et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- A systematic and comprehensive investigation of methods to build and evaluate fault prediction models
- (2009) Erik Arisholm et al. JOURNAL OF SYSTEMS AND SOFTWARE
- Conditional Variable Importance for Random Forests
- (2008) Carolin Strobl et al. BMC BIOINFORMATICS
- Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings
- (2008) S. Lessmann et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Predicting defect-prone software modules using support vector machines
- (2007) Karim O. Elish et al. JOURNAL OF SYSTEMS AND SOFTWARE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started