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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 5/2013

01.10.2013 | Original Article

On knowledge acquisition in multi-scale decision systems

verfasst von: Shen-Ming Gu, Wei-Zhi Wu

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 5/2013

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Abstract

The key to granular computing is to make use of granules in problem solving. However, there are different granules at different levels of scale in data sets having hierarchical scale structures. Therefore, the concept of multi-scale decision systems is introduced in this paper, and a formal approach to knowledge acquisition measured at different levels of granulations is also proposed, and some algorithms for knowledge acquisition in consistent and inconsistent multi-scale decision systems are proposed with illustrative examples.
Vorheriger Artikel Fast learning complex-valued classifiers for real-valued classification problems
Nächster Artikel A fuzzy taxonomy for e-Health projects

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Literatur
1.
Bargiela A, Pedrycz W (2002) Granular computing: an introduction. Kluwer Academic Publishers, Boston
2.
Bargiela A, Pedrycz W (2008) Toward a theory of granular computing for human-centered information processing. IEEE Trans Fuzzy Syst 16:320–330CrossRef
3.
Gu SM, Wu WZ, Chen HT (2007) A classification approach of granules based on variable precision rough sets. In: 6th IEEE International Conference on cognitive informatics, pp.163–168
4.
Gu SM, Zhu SX, Ye QH (2008) An approach for constructing hierarchy of granules based on fuzzy concept lattices. In: 5th International Conference on fuzzy systems and knowledge discovery, pp.679–684
5.
Hu QH, Liu JF, Yu DR (2008) Mixed feature selection based on granulation and approximation. Knowl Based Syst 21:294–304CrossRef
6.
Hu QH, Pan W, An S, Ma PJ, Wei JM (2010) An efficient gene selection technique for cancer recognition based on neighborhood mutual information. Int J Mach Learn Cybern 1:63–74CrossRef
7.
Huang GB, Wang DH, Lan Y (2011) Extreme learning machines: a survey. Int J Mach Learn Cybern 2:107–122CrossRef
8.
Inuiguchi M, Hirano S, Tsumoto S (2002) Rough set theory and granular computing. Springer, Heidelberg
9.
Komorowski J, Pawlak Z, Skowron A (1999) Rough sets: tutorial. In: Pal SK, Skowron A (eds) Rough fuzzy hybridization, a new trend in decision making, pp.3–98
10.
Leung Y, Li DY (2003) Maximal consistent block technique for rule acquisition in incomplete information systems. Inf Sci 153:85–106MathSciNetCrossRefMATH
11.
Leung Y, Zhang JS, Xu ZB (2000) Clustering by scale-space filtering. IEEE Trans Pattern Anal Mach Intell 22:1396–1410CrossRef
12.
Li DY, Zhang B, Leung Y (2004) On knowledge reduction in inconsistent decision information systems. Int J Uncertain Fuzziness Knowl Based Syst 12:651–672MathSciNetCrossRefMATH
13.
Li J, Han G, Wen J, Gao XB (2011) Robust tensor subspace learning for anomaly detection. Int J Mach Learn Cybern 2:89–98CrossRef
14.
Lin TY, Yao YY, Zadeh LA (2002) Data mining, rough sets and granular computing. Physica-Verlag, HeidelbergCrossRefMATH
15.
Ma JM, Zhang WX, Wu WZ, et al. (2007) Granular computing based on a generalized approximation space. In: Yao JT et al. (eds) RSKT 2007, LNAI 4481, pp 93–100
16.
Pawlak Z (1991) Rough sets: theoretical aspects of reasoning about data. Kluwer Academic Publishers, BostonCrossRefMATH
17.
Pawlak Z (1998) Granularity of knowledge, indiscernibility and rough sets. In: 1998 IEEE International Conference on fuzzy systems, pp. 106–110
18.
19.
Qian YH, Liang JY, Dang CY (2009) Knowledge structure, knowledge granulation and knowledge distance in a knowledge base. Int J Approx Reason 50:174–188MathSciNetCrossRefMATH
20.
Qian YH, Liang JY, Wei W (2010) Pessimistic rough decision, vol 50. In: Second International Workshop on rough sets theory, pp 440–449
21.
22.
Su J, Gao J (2003) Rough decision support method. Chin J Comput 26(6):737–745MathSciNet
23.
Su J, Gao J (2001) A meta-information-based method for incremental rough set rule generation. Pattern Recogn Artif Intell 14(4):428–433
24.
Vagin V, Fomina M (2011) Problem of knowledge discovery in noisy databases. Int J Mach Learn Cybern 2:135–145CrossRef
25.
Wu WZ (2009) Rough set approximations based on granular labels. In: Sakai H et al. (Eds.) RSFDGrC 2009, LNAI 5908, pp 93–100
26.
Wu WZ (2007) Attribute granules in formal contexts. In: An A et al. (Eds.) RSFDGrC 2007, LNAI 4482, pp 395–402
27.
Wu WZ, Leung Y (2011) Theory and applications of granular labelled partitions in multi-scale decision tables. Inf Sci 181:3878–3897CrossRefMATH
28.
Yao JT (2008) Recent developments in granular computing: a bibliometrics study. In: Proceedings of IEEE International Conference on granular computing, pp 74–79
29.
Yao YY (1999) Stratified rough sets and granular computing. In: Dave RN, Sudkamp T (eds) 18th International Conference of the North American Fuzzy Information Processing Society, pp 800–804
30.
Yao YY (2001) Information granulation and rough set approximation. Int J Intell Syst 16:87–104CrossRefMATH
31.
Yao YY (2004) A partition model of granular computing. In: Transactions on Rough Sets I. LNCS 3100, pp 232–253
32.
Yao YY, Liau CJ, Zhong N (2003) Granular computing based on rough sets, quotient space theory, and belief functions. In: Zhong N et al. (Eds.) Foundations of intelligent systems, LNAI 2871, pp 152–159
33.
Yi WG, Lu MY, Liu Z (2011) Multi-valued attribute and multilabeled data decision tree algorithm. Int J Mach Learn Cybern 2:67–74CrossRef
34.
Zadeh LA (1979) Fuzzy sets and information granularity. In: Gupta N, Ragade R, Yager RR (eds) Advances in fuzzy set theory and applications, pp 3–18
35.
Zadeh LA (1997) Towards a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst 90:111–127MathSciNetCrossRefMATH
36.
Zhang WX, Leung Y, Wu WZ (2003) Information systems and knowledge discovery (in Chinese). Science Press, Beijing
37.
Zhang WX, Mi JS, Wu WZ (2003) Approaches to knowledge reductions in inconsistent systems.. Int J Intell Syst 18:989–1000CrossRefMATH
38.
Zhao Y, Yao YY, Luo F (2007) Data analysis based on discernibility and indiscernibility. Inf Sci 177:4959–4976CrossRefMATH
Metadaten
Titel
On knowledge acquisition in multi-scale decision systems
verfasst von
Shen-Ming Gu
Wei-Zhi Wu
Publikationsdatum
01.10.2013
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 5/2013
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-012-0115-7

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