Examining difficulties software developers encounter in the adoption of statistical machine learning

Proceedings of the National Conference on Artificial Intelligence

Volumn 3, Issue , 2008, Pages 1563-1566

  Patel, Kayur ^a   Fogarty, James ^a   Landay, James A ^a,b   Harrison, Beverly ^b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b INTEL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX PROBLEMS; DO-MAINS; LABORATORY STUDIES; SOFTWARE DEVELOPERS; STATISTICAL MACHINE LEARNINGS;

APPLICATIONS; ARTIFICIAL INTELLIGENCE; BIONICS; EDUCATION; LEARNING SYSTEMS; MACHINE COMPONENTS; ROBOT LEARNING; STATISTICS;

LEARNING ALGORITHMS;

EID: 57749091415     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Fails, J.A. and Olsen, D.R. (2003). Interactive Machine Learning. International Conference on Intelligent User Interfaces (IUI 2003), 39-45.
2. Hand, D.J. (1998). Data Mining: Statistics and More? The American Statistician, 52(2), 112-1 18.
3. Ko, A.J., Myers, B.A., and Aung, H. (2004). Six Learning Barriers in End-User Programming Systems. IEEE Symposium on Visual Languages and Human-Centric Computing (VLHCC 2004), 199-206.
4. Myers, B.A., Hudson, S.E., & Pausch, R.F. (2000). Past, Present, and Future of User Interface Software Tools. ACM Transactions on Computer-Human Interaction (TOCHI), 7(1), 3-28.
5. Patel, K., Fogarty, J., Landay, J.A., & Harrison, B. (2008). Investigating Statistical Machine Learning as a Tool for Software Development. ACM Conference on Human Factors and Computing (CHI 2008), 29-38.
6. Witten, I.H., & Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. San Francisco: Morgan Kaufmann.