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[EKSX96] Ester, M.; Kriegel, H.-P.; Sander, J.; Xu, X., A density-based algorithm for discovering clusters in large spatial databases, In: Proc. 1996 Int. Conf. Knowledge Discovery and Data Mining (KDD’96) Portland, OR. (Aug. 1996), pp. 226–231.

[EKX95] Ester, M.; Kriegel, H.-P.; Xu, X., Knowledge discovery in large spatial databases: Focusing techniques for efficient class identification, In: Proc. 1995 Int. Symp. Large Spatial Databases (SSD’95) Portland, ME. (Aug. 1995), pp. 67–82.

[Elk97] Elkan, C., Boosting and naïve Bayesian learning, In: Technical Report CS97-557 (Sept. 1997) Dept. Computer Science and Engineering, University of California at San Diego.

[Elk01] Elkan, C., The foundations of cost-sensitive learning, In: Proc. 17th Intl. Joint Conf. Artificial Intelligence (IJCAI’01) Seattle, WA. (2001), pp. 973–978.

[EN10] Elmasri, R.; Navathe, S.B., Fundamentals of Database Systems. 6th ed. (2010) Addison-Wesley, Boston .

[Eng99] English, L., Improving Data Warehouse and Business Information Quality: Methods for Reducing Costs and Increasing Profits. (1999) John Wiley & Sons .

[ESAG02] Evfimievski, A.; Srikant, R.; Agrawal, R.; Gehrke, J., Privacy preserving mining of association rules, In: Proc. 2002 ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (KDD’02) Edmonton, Alberta, Canada. (July 2002), pp. 217–228.

[ET93] Efron, B.; Tibshirani, R., An Introduction to the Bootstrap. (1993) Chapman & Hall .

[FB74] Finkel, R.A.; Bentley, J.L., Quad-trees: A data structure for retrieval on composite keys, ACTA Informatica 4 (1974) 1–9.

[FB08] Friedman, J.; Bogdan, E.P., Predictive learning via rule ensembles, Ann. Applied Statistics 2 (2008) 916–954.

[FBF77] Friedman, J.H.; Bentley, J.L.; Finkel, R.A., An algorithm for finding best matches in logarithmic expected time, ACM Transactions on Math Software 3 (1977) 209–226.

[FFF99] Faloutsos, M.; Faloutsos, P.; Faloutsos, C., On power-law relationships of the internet topology, In: Proc. ACM SIGCOMM’99 Conf. Applications, Technologies, Architectures, and Protocols for Computer Communication Cambridge, MA. (Aug. 1999), pp. 251–262.

[FG02] Fishelson, M.; Geiger, D., Exact genetic linkage computations for general pedigrees, Disinformation 18 (2002) 189–198.

[FGK+05] Fagin, R.; Guha, R.V.; Kumar, R.; Novak, J.; Sivakumar, D.; Tomkins, A., Multi-structural databases, In: Proc. 2005 ACM SIGMOD-SIGACT-SIGART Symp. Principles of Database Systems (PODS’05) Baltimore, MD. (June 2005), pp. 184–195.

[FGW01] Fayyad, U.; Grinstein, G.; Wierse, A., Information Visualization in Data Mining and Knowledge Discovery. (2001) Morgan Kaufmann .

[FH51] Fix, E.; Hodges Jr., J.L., Discriminatory analysis, non-parametric discrimination: Consistency properties, In: Technical Report 21-49-004(4) (1951) USAF School of Aviation Medicine, Randolph Field, Texas.

[FH87] Fukunaga, K.; Hummels, D., Bayes error estimation using Parzen and k-nn procedure, IEEE Trans. Pattern Analysis and Machine Learning 9 (1987) 634–643.

[FH95] Fu, Y.; Han, J., 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) Singapore. (Dec. 1995), pp. 39–46.

[FI90] Fayyad, U.M.; Irani, K.B., What should be minimized in a decision tree? In: Proc. 1990 Nat. Conf. Artificial Intelligence (AAAI’90) Boston, MA. (1990), pp. 749–754.

[FI92] Fayyad, U.M.; Irani, K.B., The attribute selection problem in decision tree generation, In: Proc. 1992 Nat. Conf. Artificial Intelligence (AAAI’92) San Jose, CA. (1992), pp. 104–110.

[FI93] Fayyad, U.; Irani, K., Multi-interval discretization of continuous-valued attributes for classification learning, In: Proc. 1993 Int. Joint Conf. Artificial Intelligence (IJCAI’93) Chambery, France. (1993), pp. 1022–1029.

[Fie73] Fiedler, M., Algebraic connectivity of graphs, Czechoslovak Mathematical J. 23 (1973) 298–305.

[FL90] Fahlman, S.; Lebiere, C., The cascade-correlation learning algorithm, In: Technical