Open Access
| Issue |
ITM Web Conf.
Volume 14, 2017
The 12th International Conference Applied Mathematical Programming and Modelling – APMOD 2016
|
|
|---|---|---|
| Article Number | 00009 | |
| Number of page(s) | 16 | |
| DOI | https://doi.org/10.1051/itmconf/20171400009 | |
| Published online | 08 November 2017 | |
- A. Asuncion, D.J. Newman, UCI machine learning repository (2010), http://archive.ics.uci.edu/ml [Google Scholar]
- K.W. Bauer, S.G. Alsing, K.A. Greene, Neurocomputing 31, 29 (2000) [CrossRef] [Google Scholar]
- E.H. Han, G. Karypis, V. Kumar, B. Mobasher, Bull. Tech. Committee on Data Eng 21, 15 (1998) [Google Scholar]
- E.R. Hruschk, Feature Selection by Bayesian Networks, in Advances in Artificial Intelligence, edited by A.Y. Tawfik, S.C. Goodwin (Springer, 2004), Vol. 3060 of Lecture Notes in Artificial Intelligence, pp. 370-379 [Google Scholar]
- E.R. Hruschka, E.R. Hruschka, N.F.F. Ebecken, Missing Values Imputation for a Clustering Genetic Algorithm, in Advances in Natural Computation, edited by L.Wang, K. Chen, Y.S. Ong (Springer, 2005), Vol. 3612 of Lecture Notes in Computer Science, pp. 245–254 [CrossRef] [Google Scholar]
- W. Davies, P. Edwards, Distributed Learning: An Agent-Based Approach to Data-Mining, in Machine Learning-95, edited, by, D. Gordon (AAAI Press, 1995) [Google Scholar]
- M. A. Potter, Ph.D. thesis, George Mason University, Fairfax, Virgina (1997) [Google Scholar]
- J. E. Jackson, The American Political Science Review 65, 451 (1971) [CrossRef] [Google Scholar]
- J. Clinton, S. Jackman, D. Rivers, American Political Science Review 98, 355 (2004) [CrossRef] [Google Scholar]
- M. Cohn, ed., Congressional Quarterly Almanac 1984 (Congressional Quarterly, Washington, D. C., 1985) [Google Scholar]
- G. L. Hager, J. C. Talbert, Legislative Studies Quarterly 25, 75 (2000) [CrossRef] [Google Scholar]
- R. Fleisher, The Journal of Politics 55, 327 (1993) [CrossRef] [Google Scholar]
- M. Thomas, American Journal of Political Science 29, 96 (1985) [CrossRef] [Google Scholar]
- D. P. Green, H. L. Kern, Public opinion quarterly 76, 491 (2012) [CrossRef] [Google Scholar]
- G. R. Murray, C. Riley, A. Scime, Public Opinion Quarterly 73, 159 (2009) [CrossRef] [Google Scholar]
- H. J. Einhorn, Public Opinion Quarterly 36, 367 (1972) [CrossRef] [Google Scholar]
- J. Richman, American Political Science Review 105, 151 (2011) [CrossRef] [Google Scholar]
- J. W. Patty, American Journal of Political Science 52, 636 (2008) [CrossRef] [Google Scholar]
- E. G. Juenke, R.R. Preuhs, American Journal of Political Science 56, 705 (2012) [CrossRef] [Google Scholar]
- D. Skarbek, American Political Science Review 105, 702 (2011) [CrossRef] [Google Scholar]
- T. Hastie, R. Tibshirani, J. Friedman, The Elements of Statistical Learning, Springer Series in Statistics (Springer, New York, 2001) [Google Scholar]
- S. Milborrow, rpart.plot: plot rpart models. An enhanced version of plot.rpart (2011),http://CRAN.R-project.org/package=rpart.plot [Google Scholar]
- K. Poole, J. Lewis, J. Lo, R. Carroll, Journal of Statistical Software 42, 1 (2011) [CrossRef] [EDP Sciences] [Google Scholar]
- K. Poole, J. Lewis, 110th house roll call data, Published online (2010), http://www.voteview.com/house110.htm [Google Scholar]
- S. A. Shull, J. M. Vanderleeuw, Legislative Studies Quarterly pp. 573–582 (1987) [CrossRef] [Google Scholar]
- J. N. Victor, N. Ringe, Legislative Caucuses as Social Networks in the 110th US House of Representatives, in Networks in Political Science Conference, Cambridge, MA (2008) [Google Scholar]
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