Graphics Reference
In-Depth Information
119. Mollineda, R.A., Sánchez, J.S., Sotoca, J.M.: Data characterization for effective prototype
selection. In: Proc. of the 2nd Iberian Conf. on Pattern Recognition and Image Analysis
(ICPRIA), Lecture Notes in Computer Science, vol. 3523, pp. 27-34 (2005)
120. Narayan, B.L., Murthy, C.A., Pal, S.K.: Maxdiff kd-trees for data condensation. Pattern Recog-
nit. Lett.
27
(3), 187-200 (2006)
121. Neo, T.K.C., Ventura, D.: A direct boosting algorithm for the k-nearest neighbor classifier via
local warping of the distance metric. Pattern Recognit. Lett.
33
(1), 92-102 (2012)
122. Nikolaidis, K., Goulermas, J.Y., Wu, Q.H.: A class boundary preserving algorithm for data
condensation. Pattern Recognit.
44
(3), 704-715 (2011)
123. Nikolaidis, K., Rodriguez-Martinez, E., Goulermas, J.Y., Wu, Q.H.: Spectral graph optimiza-
tion for instance reduction. IEEE Trans. Neural Networks Learn. Syst.
23
(7), 1169-1175
(2012)
124. Nikolaidis, K., Mu, T., Goulermas, J.: Prototype reduction based on direct weighted pruning.
Pattern Recognit. Lett.
36
, 22-28 (2014)
125. Olvera-López, J.A., Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A.: Edition schemes based
on BSE. In: 10th Iberoamerican Congress on Pattern Recognition (CIARP), Lecture Notes in
Computer Science, vol. 3773, pp. 360-367 (2005)
126. Olvera-López, J.A., Carrasco-Ochoa, J.A., Martínez-Trinidad, J.F.: A new fast prototype
selection method based on clustering. Pattern Anal. Appl.
13
(2), 131-141 (2010)
127. Olvera-López, J.A., Carrasco-Ochoa, J.A., Martínez-Trinidad, J.F., Kittler, J.: A review of
instance selection methods. Artif. Intell. Rev.
34
(2), 133-143 (2010)
128. Paredes, R., Vidal, E.: Learning prototypes and distances: a prototype reduction technique
based on nearest neighbor error minimization. Pattern Recog.
39
(2), 180-188 (2006)
129. Paredes, R., Vidal, E.: Learning weighted metrics to minimize nearest-neighbor classification
error. IEEE Trans. Pattern Anal. Mach. Intell.
28
(7), 1100-1110 (2006)
130. García-Pedrajas, N.: Evolutionary computation for training set selection. Wiley Interdisc.
Rev.: Data Min. Knowl. Disc.
1
(6), 512-523 (2011)
131. Pekalska, E., Duin, R.P.W., Paclík, P.: Prototype selection for dissimilarity-based classifiers.
Pattern Recognit.
39
(2), 189-208 (2006)
132. Raniszewski, M.: Sequential reduction algorithm for nearest neighbor rule. In: ICCVG (2),
Lecture Notes in Computer Science, vol. 6375, pp. 219-226. Springer, Heidelberg (2010)
133. Reinartz, T.: A unifying view on instance selection. Data Min. Knowl. Disc.
6
(2), 191-210
(2002)
134. Calana, Y.P., Reyes, E.G., Alzate, M.O., Duin, R.P.W.: Prototype selection for dissimilarity
representation by a genetic algorithm. In: International Conference on Pattern Recogition
(ICPR), pp. 177-180 (2010)
135. Riquelme, J.C., Aguilar-Ruiz, J.S., Toro, M.: Finding representative patterns with ordered
projections. Pattern Recognit.
36
(4), 1009-1018 (2003)
136. Ritter, G.L., Woodruff, H.B., Lowry, S.R., Isenhour, T.L.: An algorithm for a selective nearest
neighbor decision rule. IEEE Trans. Inf. Theory
25
, 665-669 (1975)
137. Sáez, J.A., Luengo, J., Herrera, F.: Predicting noise filtering efficacy with data complexity
measures for nearest neighbor classification. Pattern Recognit.
46
(1), 355-364 (2013)
138. Salzberg, S.: A nearest hyperrectangle learning method. Mach. Learn.
6
, 251-276 (1991)
139. Sánchez, J.S., Pla, F., Ferri, F.J.: Prototype selection for the nearest neighbor rule through
proximity graphs. Pattern Recognit. Lett.
18
, 507-513 (1997)
140. Sánchez, J.S., Barandela, R., Marqués, A.I., Alejo, R., Badenas, J.: Analysis of new techniques
to obtain quality training sets. Pattern Recognit. Lett.
24
(7), 1015-1022 (2003)
141. Sánchez, J.S.: High training set size reduction by space partitioning and prototype abstraction.
Pattern Recognit.
37
(7), 1561-1564 (2004)
142. Dos Santos, E.M., Sabourin, R., Maupin, P.: Overfitting cautious selection of classifier ensem-
bles with genetic algorithms. Inf. Fusion
10
(2), 150-162 (2009)
143. Sebban, M., Nock, R.: Instance pruning as an information preserving problem. In: ICML '00:
Proceedings of the Seventeenth International Conference on Machine Learning, pp. 855-862
(2000)
