The PROMISE repository of empirical software engineering data G Boetticher http://promisedata. org/repository, 2007 | 320 | 2007 |
Molecular phenotyping of severe asthma using pattern recognition of bronchoalveolar lavage–derived cytokines AR Brasier, S Victor, G Boetticher, H Ju, C Lee, ER Bleecker, M Castro, ... Journal of Allergy and Clinical Immunology 121 (1), 30-37. e6, 2008 | 151 | 2008 |
An assessment of metric contribution in the construction of a neural network-based effort estimator G Boetticher Second International Workshop on Soft Computing Applied to Software …, 2001 | 65 | 2001 |
A neural net-based approach to software metrics G Boetticher, K Srinivas, DA Eichmann Research Inst. for Computing and Information Systems, The SoRReL Papers …, 1992 | 59 | 1992 |
A neural network paradigm for characterizing reusable software G Boetticher, D Eichmann Research Institute for Computing and Information Systems, University of …, 1993 | 56 | 1993 |
Using machine learning to predict project effort: Empirical case studies in data-starved domains G Boetticher Proceedings of the First International Workshop on Model-Based Requirements …, 2001 | 49 | 2001 |
The PROMISE repository of empirical software engineering data, 2007 G Boetticher, T Menzies, T Ostrand | 39 | 2007 |
Nearest neighbor sampling for better defect prediction GD Boetticher ACM SIGSOFT Software Engineering Notes 30 (4), 1-6, 2005 | 34 | 2005 |
PROMISE Repository of Empirical Software Engineering Data, West Virginia University, Department of Computer Science, 2007 G Boetticher, T Menzies, T Ostrand | 30 | |
Improving credibility of machine learner models in software engineering GD Boetticher Advances in Machine Learning Applications in Software Engineering, 52-72, 2007 | 28 | 2007 |
Building a genetically engineerable evolvable program (GEEP) using breadth-based explicit knowledge for predicting software defects K Kaminsky, G Boetticher IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS'04. 1 …, 2004 | 19 | 2004 |
Teaching financial data mining using stocks and futures contracts GD Boetticher Journal of Systemic, Cybernetics and Informatics 3 (3), 26-32, 2006 | 18 | 2006 |
Using a pre-assessment exam to construct an effective concept-based genetic program for predicting course success GD Boetticher, W Ding, C Moen, KB Yue ACM SIGCSE Bulletin 37 (1), 500-504, 2005 | 15 | 2005 |
Applying machine learners to GUI specifications in formulating early life cycle project estimations GD Boetticher Software Engineering with Computational Intelligence, 1-16, 2003 | 14 | 2003 |
How to predict more with less, defect prediction using machine learners in an implicitly data starved domain K Kaminsky, G Boetticher The 8th world multiconference on systemics, cybernetics and informatics …, 2004 | 12 | 2004 |
Smarter software engineering: Practical data mining approaches T Menzies, GD Boetticher 27th Annual NASA Goddard Software Engineering Workshop, 2002. Proceedings. 1 …, 2002 | 10 | 2002 |
When will it be done? the 300 billion dollar question, machine learner answers G Boetticher IEEE Intelligent Systems 18 (3), 48-50, 2003 | 9 | 2003 |
Better software defect prediction using equalized learning with machine learners K Kaminsky, GD Boetticher Knowledge Sharing and Collaborative Engineering, 2004 | 8 | 2004 |
Assessing the reliability of a human estimator GD Boetticher, N Lokhandwala Third International Workshop on Predictor Models in Software Engineering …, 2007 | 7 | 2007 |
Understanding the human estimator G Boetticher, N Lokhandwala, J Helm Second International Predictive Models in Software Engineering (PROMISE …, 2006 | 7 | 2006 |