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Erschienen in: Soft Computing 9/2016

18.06.2015 | Methodologies and Application

MFlexDT: multi flexible fuzzy decision tree for data stream classification

verfasst von: Ayaz Isazadeh, Farnaz Mahan, Witold Pedrycz

Erschienen in: Soft Computing | Ausgabe 9/2016

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Abstract

In many real-world applications, instances (data) arrive sequentially in the form of streams. Processing such data poses challenges to machine learning. While adhering to on-line learning strategies, in this paper we extend the Flexible Fuzzy Decision Tree (FlexDT) algorithm with multiple partitioning that makes it possible to carry out automatic on-line fuzzy data classification. The proposed method is aimed to balance accuracy and tree size in data stream mining. The objective of the classification problem is to predict the true class of each incoming instances in real time. In terms of evaluation of the method, accuracy, tree depth, and the learning time are significant factors influencing the performance. A series of experiments demonstrate that the proposed method produces optimal trees for both numeric and nominal features (variables).

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Literatur
Zurück zum Zitat Afsari F, Eftekhari M, Eslami E, Woo P-Y (2013) Interpretability-based fuzzy decision tree classifier a hybrid of the subtractive clustering and the multi-objective evolutionary algorithm. Soft Comput 17(9):1673–1686CrossRef Afsari F, Eftekhari M, Eslami E, Woo P-Y (2013) Interpretability-based fuzzy decision tree classifier a hybrid of the subtractive clustering and the multi-objective evolutionary algorithm. Soft Comput 17(9):1673–1686CrossRef
Zurück zum Zitat Ahila R, Sadasivam V (2014) Performance enhancement of extreme learning machine for power system disturbances classification. Soft Comput 18(2):239–253CrossRef Ahila R, Sadasivam V (2014) Performance enhancement of extreme learning machine for power system disturbances classification. Soft Comput 18(2):239–253CrossRef
Zurück zum Zitat Badr S, Bargiela A (2011) Case study of inaccuracies in the granulation of decision trees. Soft Comput 15(6):1129–1136CrossRef Badr S, Bargiela A (2011) Case study of inaccuracies in the granulation of decision trees. Soft Comput 15(6):1129–1136CrossRef
Zurück zum Zitat Bifet A, Holmes G, Kirkby R, Pfahringe B (2010) MOA: massive online analysis. J Mach Learn Res 11:1601–1604 Bifet A, Holmes G, Kirkby R, Pfahringe B (2010) MOA: massive online analysis. J Mach Learn Res 11:1601–1604
Zurück zum Zitat Bifet A, Holmes G, Pfahringer B, Kirkby R, Gavald‘a R (2009) New ensemble methods for evolving data streams. In: Proceedings of the 15th ACMSIGKDD international conference on knowledge discovery and data mining (KDD’09). ACM, Paris, pp 139–147 Bifet A, Holmes G, Pfahringer B, Kirkby R, Gavald‘a R (2009) New ensemble methods for evolving data streams. In: Proceedings of the 15th ACMSIGKDD international conference on knowledge discovery and data mining (KDD’09). ACM, Paris, pp 139–147
Zurück zum Zitat Bifet A, Kirkby R (2009) Data stream mining a practical approach. University of Waikata Bifet A, Kirkby R (2009) Data stream mining a practical approach. University of Waikata
Zurück zum Zitat Bouchachia A (2011) Fuzzy classification in dynamic environments. Soft Comput 15(5):1009–1022CrossRef Bouchachia A (2011) Fuzzy classification in dynamic environments. Soft Comput 15(5):1009–1022CrossRef
Zurück zum Zitat Browne A, Hudson B, Whitley D, Ford M, Picton P (2004) Biological data mining with neural networks: implementation and application of a flexible decision tree extraction algorithm to genomic problem domains. Neurocomputing J 57:275–293CrossRef Browne A, Hudson B, Whitley D, Ford M, Picton P (2004) Biological data mining with neural networks: implementation and application of a flexible decision tree extraction algorithm to genomic problem domains. Neurocomputing J 57:275–293CrossRef
Zurück zum Zitat Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(1):37–46CrossRef Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(1):37–46CrossRef
Zurück zum Zitat Evans L, Lohse N, Summers M (2013) A fuzzy-decision-tree approach for manufacturing technology selection exploiting experience-based information. In: Expert systems with applications, vol 40, issue 16, pp 6412–6426 Evans L, Lohse N, Summers M (2013) A fuzzy-decision-tree approach for manufacturing technology selection exploiting experience-based information. In: Expert systems with applications, vol 40, issue 16, pp 6412–6426
Zurück zum Zitat Gama J, Gaber M (2007) Medhat., predictive learning in sensor networks. In: Chapter 10 of learning from data streams—Processing techniques in sensor networks. Springer, Berlin, pp 143–164 Gama J, Gaber M (2007) Medhat., predictive learning in sensor networks. In: Chapter 10 of learning from data streams—Processing techniques in sensor networks. Springer, Berlin, pp 143–164
Zurück zum Zitat Gomes JB, Gaber MM, Sousa PAC, Menasalvas E (2014) Mining recurring concepts in a dynamic feature space. Neural Netw Learn Syst IEEE Trans 25(1):95–110CrossRef Gomes JB, Gaber MM, Sousa PAC, Menasalvas E (2014) Mining recurring concepts in a dynamic feature space. Neural Netw Learn Syst IEEE Trans 25(1):95–110CrossRef
Zurück zum Zitat Hamzeia Shah GH, Mulvaneya DJ (1999) On-line learning of fuzzy decision trees for global path planning. Eng Appl Artif Intell 12(1):93–109CrossRef Hamzeia Shah GH, Mulvaneya DJ (1999) On-line learning of fuzzy decision trees for global path planning. Eng Appl Artif Intell 12(1):93–109CrossRef
Zurück zum Zitat Hashemi S, Yang Y (2009) Flexible decision tree for data stream classification in the presence of concept change, noise and missing values. Data Min Knowl Discov J 19:95–131MathSciNetCrossRef Hashemi S, Yang Y (2009) Flexible decision tree for data stream classification in the presence of concept change, noise and missing values. Data Min Knowl Discov J 19:95–131MathSciNetCrossRef
Zurück zum Zitat Hoeglinger S, Pears R (2007) Use of Hoeffding trees in concept based data stream mining. In: Third International conference on information and automation for sustainability, pp 57–62 Hoeglinger S, Pears R (2007) Use of Hoeffding trees in concept based data stream mining. In: Third International conference on information and automation for sustainability, pp 57–62
Zurück zum Zitat Hulten G, Spencer L, Domingos P (2001) Mining time-changing data streams. In: Proceedings of the 7th ACM SIGKDD international conference on knowledge discovery and data mining (SIGKDD), pp 97–106 Hulten G, Spencer L, Domingos P (2001) Mining time-changing data streams. In: Proceedings of the 7th ACM SIGKDD international conference on knowledge discovery and data mining (SIGKDD), pp 97–106
Zurück zum Zitat Khanli LM, Analoui M (2009) Active grid information server for grid computing. J Supercomput 50(1):19–35 Khanli LM, Analoui M (2009) Active grid information server for grid computing. J Supercomput 50(1):19–35
Zurück zum Zitat Kranen P (2011) Anytime algorithms for stream data mining. Doctoral Theses, RWTH Aachen University Kranen P (2011) Anytime algorithms for stream data mining. Doctoral Theses, RWTH Aachen University
Zurück zum Zitat Li D, Gu H, Zhang L (2013) A hybrid genetic algorithm–fuzzy c-means approach for incomplete data clustering based on nearest-neighbor intervals. Soft Comput 17(10):1787–1796CrossRef Li D, Gu H, Zhang L (2013) A hybrid genetic algorithm–fuzzy c-means approach for incomplete data clustering based on nearest-neighbor intervals. Soft Comput 17(10):1787–1796CrossRef
Zurück zum Zitat Luengo J, Sez JA, Herrera F (2012) Missing data imputation for fuzzy rule-based classification systems. Soft Comput 16(5):863–881CrossRef Luengo J, Sez JA, Herrera F (2012) Missing data imputation for fuzzy rule-based classification systems. Soft Comput 16(5):863–881CrossRef
Zurück zum Zitat Milln-Giraldo M, Salvador Snchez J, Javier Traver V (2011) On-line learning from streaming data with delayed attributes: a comparison of classifiers and strategies. Neural Comput Appl 20(7):935–944CrossRef Milln-Giraldo M, Salvador Snchez J, Javier Traver V (2011) On-line learning from streaming data with delayed attributes: a comparison of classifiers and strategies. Neural Comput Appl 20(7):935–944CrossRef
Zurück zum Zitat Mitra S, Pal S, Mitra P (2002) Data mining in soft computing framework: a survery. IEEE Trans Neural Netw 13(1):3–14 Mitra S, Pal S, Mitra P (2002) Data mining in soft computing framework: a survery. IEEE Trans Neural Netw 13(1):3–14
Zurück zum Zitat Nauck DD (2004) Neuro-fuzzy learning with symbolic and numeric data. Soft Comput 8(6):383–396CrossRef Nauck DD (2004) Neuro-fuzzy learning with symbolic and numeric data. Soft Comput 8(6):383–396CrossRef
Zurück zum Zitat Olaru C, Wehenkel L (2003) A complete fuzzy decision tree technique. Fuzzy Sets Syst 138(2):221–254 Olaru C, Wehenkel L (2003) A complete fuzzy decision tree technique. Fuzzy Sets Syst 138(2):221–254
Zurück zum Zitat Orriols-Puig A, Casillas J (2011) Fuzzy knowledge representation study for incremental learning in data streams and classification problems. Soft Comput 15(12):2389–2414CrossRef Orriols-Puig A, Casillas J (2011) Fuzzy knowledge representation study for incremental learning in data streams and classification problems. Soft Comput 15(12):2389–2414CrossRef
Zurück zum Zitat Sugumaran V, Nair B (2010) Comparison of decision tree-fuzzy and rough set-fuzzy methods for fault categorization of mono-block centrifugal pump. Mech Syst Signal Process J 24(6):1887–1906CrossRef Sugumaran V, Nair B (2010) Comparison of decision tree-fuzzy and rough set-fuzzy methods for fault categorization of mono-block centrifugal pump. Mech Syst Signal Process J 24(6):1887–1906CrossRef
Zurück zum Zitat Weiqing J (2005) Fuzzy classification based on fuzzy association rule mining. Ph.D thessis of Philosophy, Graduate Faculty of North Carolina State University Weiqing J (2005) Fuzzy classification based on fuzzy association rule mining. Ph.D thessis of Philosophy, Graduate Faculty of North Carolina State University
Zurück zum Zitat Wenerstrom B, Giraud-Carrier C (2007) Temporal data mining in dynamic feature spaces. In: Proceedings of 6th international conference data mining, pp 1141–1145 Wenerstrom B, Giraud-Carrier C (2007) Temporal data mining in dynamic feature spaces. In: Proceedings of 6th international conference data mining, pp 1141–1145
Zurück zum Zitat Yang H, Fong S (2011) Moderated VFDT in stream mining using adaptive tie threshold and incremental pruning. In: Proceedings of the 13th international conference on data warehousing and knowledge discovery (DaWaK’11). Springer, Toulouse, pp 471–483 Yang H, Fong S (2011) Moderated VFDT in stream mining using adaptive tie threshold and incremental pruning. In: Proceedings of the 13th international conference on data warehousing and knowledge discovery (DaWaK’11). Springer, Toulouse, pp 471–483
Zurück zum Zitat Yang H, Fong S (2013) Incremental optimization mechanism for constructing a decision tree in data stream mining. Math Probl Eng 2013. doi:10.1155/2013/580397 Yang H, Fong S (2013) Incremental optimization mechanism for constructing a decision tree in data stream mining. Math Probl Eng 2013. doi:10.​1155/​2013/​580397
Zurück zum Zitat Yao Z, Lou G, Song X, Zhou Y (2010) On-line fault diagnosis study for roller bearing based on fuzzy fault tree. In: Informatics in control, automation and robotics (CAR). Proceeding of 2010 2nd international Asia conference. China, pp 182–185 Yao Z, Lou G, Song X, Zhou Y (2010) On-line fault diagnosis study for roller bearing based on fuzzy fault tree. In: Informatics in control, automation and robotics (CAR). Proceeding of 2010 2nd international Asia conference. China, pp 182–185
Zurück zum Zitat Zhai JH (2011) Fuzzy decision tree based on fuzzy-rough technique. Soft Comput 15(6):1087–1096CrossRef Zhai JH (2011) Fuzzy decision tree based on fuzzy-rough technique. Soft Comput 15(6):1087–1096CrossRef
Zurück zum Zitat Zhang D (2012) A new approach and system for attentive mobile learning based on seamless migration. Appl Intell 36(1):75–89CrossRef Zhang D (2012) A new approach and system for attentive mobile learning based on seamless migration. Appl Intell 36(1):75–89CrossRef
Zurück zum Zitat Zhang D, Li G, Zheng K (2014) An energy-balanced routing method based on forward-aware factor for wireless sensor network. IEEE Trans Ind Inf 10(1):766–773CrossRef Zhang D, Li G, Zheng K (2014) An energy-balanced routing method based on forward-aware factor for wireless sensor network. IEEE Trans Ind Inf 10(1):766–773CrossRef
Zurück zum Zitat Zhang D, Wang X, Song X (2014) A novel approach to mapped correlation of ID for RFID anti-collision. IEEE Trans Serv Comput 7(4):741–748MathSciNetCrossRef Zhang D, Wang X, Song X (2014) A novel approach to mapped correlation of ID for RFID anti-collision. IEEE Trans Serv Comput 7(4):741–748MathSciNetCrossRef
Zurück zum Zitat Zhang D, Dan Zhang X (2012) Design and implementation of embedded un-interruptible power supply system (EUPSS) for web-based mobile application. Enterprise IS 6(4):473–489CrossRef Zhang D, Dan Zhang X (2012) Design and implementation of embedded un-interruptible power supply system (EUPSS) for web-based mobile application. Enterprise IS 6(4):473–489CrossRef
Zurück zum Zitat Zhang D, Zhu Y (2012) A new constructing approach for a weighted topology of wireless sensor networks based on local-world theory for the internet of things (IOT). Comput Math Appl 64(5):1044–1055CrossRef Zhang D, Zhu Y (2012) A new constructing approach for a weighted topology of wireless sensor networks based on local-world theory for the internet of things (IOT). Comput Math Appl 64(5):1044–1055CrossRef
Metadaten
Titel
MFlexDT: multi flexible fuzzy decision tree for data stream classification
verfasst von
Ayaz Isazadeh
Farnaz Mahan
Witold Pedrycz
Publikationsdatum
18.06.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 9/2016
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-015-1733-2

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