Databases Reference
In-Depth Information
[FGK
C
05]
R. Fagin, R. V. Guha, R. Kumar, J. Novak, D. Sivakumar, and A. Tomkins. Multi-
structural databases. In
Proc. 2005 ACM SIGMOD-SIGACT-SIGART Symp. Principles
of Database Systems (PODS'05)
, pp. 184-195, Baltimore, MD, June 2005.
[FGW01]
U. Fayyad, G. Grinstein, and A. Wierse.
Information Visualization in Data Mining and
Knowledge Discovery
. Morgan Kaufmann, 2001.
[FH51]
E. Fix and J. L. Hodges Jr. Discriminatory analysis, non-parametric discrimination:
Consistency properties. In
Technical Report 21-49-004(4)
, USAF School of Aviation
Medicine, Randolph Field, Texas, 1951.
[FH87]
K. Fukunaga and D. Hummels. Bayes error estimation using Parzen and
k-nn
procedure.
IEEE Trans. Pattern Analysis and Machine Learning
, 9:634-643, 1987.
[FH95]
Y. Fu and J. Han. Meta-rule-guided mining of association rules in relational databases. In
Proc. 1995 Int. Workshop Integration of Knowledge Discovery with Deductive and Object-
Oriented Databases (KDOOD'95)
, pp. 39-46, Singapore, Dec. 1995.
[FI90]
U. M. Fayyad and K. B. Irani. What should be minimized in a decision tree? In
Proc.
1990 Nat. Conf. Artificial Intelligence (AAAI'90)
, pp. 749-754, Boston, MA, 1990.
[FI92]
U. M. Fayyad and K. B. Irani. The attribute selection problem in decision tree gener-
ation. In
Proc. 1992 Nat. Conf. Artificial Intelligence (AAAI'92)
, pp. 104-110, San Jose,
CA, 1992.
[FI93]
U. Fayyad and K. Irani. Multi-interval discretization of continuous-valued attributes
for classification learning. In
Proc. 1993 Int. Joint Conf. Artificial Intelligence (IJCAI'93)
,
pp. 1022-1029, Chambery, France, 1993.
[Fie73]
M. Fiedler. Algebraic connectivity of graphs.
Czechoslovak Mathematical J.
, 23:298-305,
1973.
[FL90]
S. Fahlman and C. Lebiere. The cascade-correlation learning algorithm. In
Technical
Report CMU-CS-90-100
, Computer Sciences Department, Carnegie Mellon University,
1990.
[FL95]
C. Faloutsos and K.-I. Lin. FastMap: A fast algorithm for indexing, data-mining and
visualization of traditional and multimedia datasets. In
Proc. 1995 ACM-SIGMOD Int.
Conf. Management of Data (SIGMOD'95)
, pp. 163-174, San Jose, CA, May 1995.
[Fle87]
R. Fletcher.
Practical Methods of Optimization
. John Wiley & Sons, 1987.
[FMMT96]
T. Fukuda, Y. Morimoto, S. Morishita, and T. Tokuyama. Data mining using two-
dimensional optimized association rules: Scheme, algorithms, and visualization. In
Proc. 1996 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD'96)
, pp. 13-23,
Montreal, Quebec, Canada, June 1996.
[FP05]
J. Friedman and B. E. Popescu. Predictive learning via rule ensembles. In
Technical
Report
, Department of Statistics, Stanford University, 2005.
[FPP07]
D. Freedman, R. Pisani, and R. Purves.
Statistics
(4th ed.). W. W. Norton & Co., 2007.
[FPSS+96]
U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy (eds.).
Advances in
Knowledge Discovery and Data Mining
. AAAI/MIT Press, 1996.
[FP97]
T. Fawcett and F. Provost.
Adaptive fraud detection.
Data Mining and Knowledge
Discovery
, 1:291-316, 1997.
[FR02]
C. Fraley and A. E. Raftery. Model-based clustering, discriminant analysis, and density
estimation.
J. American Statistical Association
, 97:611-631, 2002.
