Graphics Reference
In-Depth Information
95. Kim, S.W., Oommen, B.J.: On using prototype reduction schemes to optimize dissimilarity-
based classification. Pattern Recognit.
40
(11), 2946-2957 (2007)
96. Kim, S.W., Oommen, B.J.: On using prototype reduction schemes to enhance the computation
of volume-based inter-class overlap measures. Pattern Recognit.
42
(11), 2695-2704 (2009)
97. Kim, S.W.: An empirical evaluation on dimensionality reduction schemes for dissimilarity-
based classifications. Pattern Recogn. Lett.
32
(6), 816-823 (2011)
98. Kohonen, T.: The self organizing map. Proc. IEEE
78
(9), 1464-1480 (1990)
99. Koplowitz, J., Brown, T.: On the relation of performance to editing in nearest neighbor rules.
Pattern Recognit.
13
, 251-255 (1981)
100. Kuncheva, L.I.: Editing for the k-nearest neighbors rule by a genetic algorithm. Pattern
Recogn. Lett.
16
(8), 809-814 (1995)
101. Kuncheva, L.I., Jain, L.C.: Nearest neighbor classifier: simultaneous editing and feature selec-
tion. Pattern Recogn. Lett.
20
(11-13), 1149-1156 (1999)
102. Lam, W., Keung, C.K., Liu, D.: Discovering useful concept prototypes for classification based
on filtering and abstraction. IEEE Trans. Pattern Anal. Mach. Intell.
14
(8), 1075-1090 (2002)
103. Leyva, E., González, A., Pérez, R.: Knowledge-based instance selection: a compromise
between efficiency and versatility. Knowl.-Based Syst.
47
, 65-76 (2013)
104. Li, Y., Hu, Z., Cai, Y., Zhang, W.: Support vector based prototype selection method for
nearest neighbor rules. In: First International Conference on Advances in Natural Computation
(ICNC), Lecture Notes in Computer Science, vol. 3610, pp. 528-535 (2005)
105. Li, Y., Maguire, L.P.: Selecting critical patterns based on local geometrical and statistical
information. IEEE Trans. Pattern Anal. Mach. Intell.
33
(6), 1189-1201 (2011)
106. Li, I.J., Chen, J.C., Wu, J.L.: A fast prototype reduction method based on template reduction
and visualization-induced self-organizing map for nearest neighbor algorithm. Appl. Intell.
39
(3), 564-582 (2013)
107. Lipowezky, U.: Selection of the optimal prototype subset for 1-nn classification. Pattern
Recogn. Lett.
19
(10), 907-918 (1998)
108. Liu, H., Motoda, H.: Instance Selection and Construction for Data Mining. Kluwer Academic
Publishers, Norwell (2001)
109. Liu, H., Motoda, H.: On issues of instance selection. Data Min. Knowl. Disc.
6
(2), 115-130
(2002)
110. López, V., Fernández, A., García, S., Palade, V., Herrera, F.: An insight into classification with
imbalanced data: empirical results and current trends on using data intrinsic characteristics.
Inf. Sci.
250
, 113-141 (2013)
111. Lowe, D.G.: Similarity metric learning for a variable-kernel classifier. Neural Comput.
7
(1),
72-85 (1995)
112. Lozano, M.T., Sánchez, J.S., Pla, F.: Using the geometrical distribution of prototypes for
training set condensing. CAEPIA, Lecture Notes in Computer Science, vol. 3040, pp. 618-
627 (2003)
113. Lozano, M., Sotoca, J.M., Sánchez, J.S., Pla, F., Pekalska, E., Duin, R.P.W.: Experimental
study on prototype optimisation algorithms for prototype-based classification in vector spaces.
Pattern Recognit.
39
(10), 1827-1838 (2006)
114. Luaces, O., Bahamonde, A.: Inflating examples to obtain rules. Int. J. Intell. syst.
18
, 1113-
1143 (2003)
115. Luengo, J., Fernández, A., García, S., Herrera, F.: Addressing data complexity for imbal-
anced data sets: analysis of smote-based oversampling and evolutionary undersampling. Soft
Comput.
15
(10), 1909-1936 (2011)
116. Marchiori, E.: Hit miss networks with applications to instance selection. J. Mach. Learn. Res.
9
, 997-1017 (2008)
117. Marchiori, E.: Class conditional nearest neighbor for large margin instance selection. IEEE
Trans. Pattern Anal. Mach. Intell.
32
, 364-370 (2010)
118. Miloud-Aouidate, A., Baba-Ali, A.R.: Ant colony prototype reduction algorithm for knn
classification. In: International Conference on Computational Science and Engineering, pp.
289-294 (2012)
