Evaluation of feature selection methods for text classification with small datasets using multiple criteria decision-making methods
The evaluation of feature selection methods for text classification with small sample datasets must consider classification performance, stability, and efficiency. It is, thus, a multiple criteria decision-making (MCDM) problem. Yet there has been few research in feature selection evaluation using M...
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| Published in | Applied soft computing Vol. 86; p. 105836 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.01.2020
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| Subjects | |
| Online Access | Get full text |
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| Abstract | The evaluation of feature selection methods for text classification with small sample datasets must consider classification performance, stability, and efficiency. It is, thus, a multiple criteria decision-making (MCDM) problem. Yet there has been few research in feature selection evaluation using MCDM methods which considering multiple criteria. Therefore, we use MCDM-based methods for evaluating feature selection methods for text classification with small sample datasets. An experimental study is designed to compare five MCDM methods to validate the proposed approach with 10 feature selection methods, nine evaluation measures for binary classification, seven evaluation measures for multi-class classification, and three classifiers with 10 small datasets. Based on the ranked results of the five MCDM methods, we make recommendations concerning feature selection methods. The results demonstrate the effectiveness of the used MCDM-based method in evaluating feature selection methods.
•Evaluating feature selection methods for text classification with small datasets.•Comparing five MCDM-based methods to validate the proposed approach.•Providing recommendation of feature selection methods. |
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| AbstractList | The evaluation of feature selection methods for text classification with small sample datasets must consider classification performance, stability, and efficiency. It is, thus, a multiple criteria decision-making (MCDM) problem. Yet there has been few research in feature selection evaluation using MCDM methods which considering multiple criteria. Therefore, we use MCDM-based methods for evaluating feature selection methods for text classification with small sample datasets. An experimental study is designed to compare five MCDM methods to validate the proposed approach with 10 feature selection methods, nine evaluation measures for binary classification, seven evaluation measures for multi-class classification, and three classifiers with 10 small datasets. Based on the ranked results of the five MCDM methods, we make recommendations concerning feature selection methods. The results demonstrate the effectiveness of the used MCDM-based method in evaluating feature selection methods.
•Evaluating feature selection methods for text classification with small datasets.•Comparing five MCDM-based methods to validate the proposed approach.•Providing recommendation of feature selection methods. |
| ArticleNumber | 105836 |
| Author | Chen, Yang Kou, Gang Peng, Yi Xiao, Feng Alsaadi, Fawaz E. Yang, Pei |
| Author_xml | – sequence: 1 givenname: Gang orcidid: 0000-0002-9220-8647 surname: Kou fullname: Kou, Gang organization: School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China – sequence: 2 givenname: Pei surname: Yang fullname: Yang, Pei organization: School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China – sequence: 3 givenname: Yi orcidid: 0000-0003-0373-6665 surname: Peng fullname: Peng, Yi email: pengyi@uestc.edu.cn organization: School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China – sequence: 4 givenname: Feng orcidid: 0000-0003-3412-5816 surname: Xiao fullname: Xiao, Feng organization: School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China – sequence: 5 givenname: Yang surname: Chen fullname: Chen, Yang organization: School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China – sequence: 6 givenname: Fawaz E. surname: Alsaadi fullname: Alsaadi, Fawaz E. organization: Department of information Technology, Faculty of Computing and IT, King Abdulaziz University, Jeddah, Saudi Arabia |
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| Cites_doi | 10.1016/j.ins.2017.08.036 10.1016/0030-5073(81)90015-5 10.1016/j.eswa.2014.10.011 10.1109/TSMC.2018.2841063 10.1186/s40854-019-0138-0 10.1007/s10462-009-9124-7 10.1016/j.eswa.2010.09.153 10.1016/j.ins.2014.02.137 10.1016/j.ipm.2011.12.005 10.1016/j.ipm.2004.08.006 10.1016/j.patrec.2008.08.010 10.3846/20294913.2014.892037 10.1016/j.asoc.2010.11.028 10.1023/A:1007692713085 10.1016/j.eswa.2008.08.022 10.1016/j.ins.2016.08.073 10.1186/s40854-019-0131-7 10.1016/j.eswa.2014.12.013 10.1016/j.eswa.2015.08.050 10.1016/j.eswa.2012.05.008 10.1142/S0219622012500095 10.3846/20294913.2016.1210694 10.1016/j.csda.2013.07.012 10.1109/TSMC.2015.2422267 10.1016/j.patcog.2015.02.025 10.1186/s40854-019-0125-5 10.1016/j.neucom.2015.01.031 10.1186/s40854-018-0086-0 10.1016/j.knosys.2012.06.005 10.1145/505282.505283 10.1016/j.ipm.2009.03.002 10.1016/j.ejor.2019.03.009 10.1016/j.ejor.2013.11.035 10.1016/j.eswa.2008.06.054 10.1186/s40854-019-0144-2 10.1109/TPAMI.2010.34 10.1016/j.omega.2011.01.009 10.1016/j.ins.2015.06.033 10.1016/j.cie.2007.12.002 10.1016/j.eswa.2006.04.001 10.1016/j.knosys.2013.09.019 10.1016/j.knosys.2011.04.014 10.1016/j.ejor.2013.10.019 10.1016/j.eswa.2013.02.019 10.1111/1467-8667.00269 10.1007/s10115-006-0040-8 10.1016/j.inffus.2016.11.012 |
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| References | Chen, Huang, Tian (b48) 2009; 36 Uysal, Gunal (b18) 2012; 36 Toloie-Eshlaghy, Homayonfar (b34) 2011 Opricovic (b52) 1998; 2 Ogura, Amano, Kondo (b31) 2011; 38 Peng, Fan (b6) 2017; 418–419 Taşcı, Güngör (b14) 2013; 40 Kuo, Yang, Huang (b12) 2008; 55 P. Bo, L. Lee, Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales (2005), pp. 115–124. Sebastiani (b3) 2001; 34 Shang, Li, Feng (b7) 2013; 54 Maas, Daly, Pham (b55) 2011 Aghdam, Ghasem-Aghaee, Basiri (b29) 2009; 36 Pinheiro, Cavalcanti, Correa (b32) 2012; 39 Mesterharm, M.J. (b56) 2011 Shang, Huang, Zhu (b17) 2007; 33 Zhang, Kou, Peng (b36) 2019; 277 Cortes (b25) 2004 Y. Saeys, T. Abeel, Y.V.D. Peer, Robust feature selection using ensemble feature selection techniques, in: Machine Learning and Knowledge Discovery in Databases, European Conference, Ecml/pkdd 2008, Antwerp, Belgium, September (2008) 15-19, Proceedings, DBLP, 2008, pp. 313–325. Uğuz (b19) 2011; 24 Kou, Lin (b38) 2014; 235 Zeng, Zhang, Zhang (b8) 2015; 48 Rosset (b26) 2004 Selvamuthu, Kumar, Mishra (b59) 2019; 5 Kou, Ergu, Lin (b39) 2016; 22 Stillwell, Seaver, Edwards (b62) 1981; 28 Alias, Hashim, Samsudin (b44) 2008 Fazelabdolabadi (b61) 2019; 5 Rehman, Javed, Babri (b20) 2015; 42 Liu, Bi, Fan (b41) 2017; 36 Peng, Wang, Kou (b46) 2011; 11 Zhong, Enke (b5) 2019; 5 Somol, Novovicová (b9) 2010; 32 Singh, Kumar, Singla (b43) 2013; 5 Rokach (b45) 2010; 33 Uysal (b22) 2016; 43 Yang, Pedersen (b15) 1997 Pinheiro, Cavalcanti, Ren (b21) 2015; 42 Li, Kou, Peng (b35) 2016 Davis, Goadrich (b27) 2006 Lee, Lee (b16) 2006; 42 Peng, Kou, Wang (b42) 2011; 39 Dernoncourt, Hanczar, Zucker (b10) 2014; 71 Nigam, Mccallum, Thrun (b49) 2000; 39 Junejo, Karim, Hassan (b2) 2016; 372 Song, Wang, Zhu (b60) 2018; 4 Opricovic, Tzeng (b53) 2010; 17 Kou, Lu, Peng (b47) 2012; 11 Yang, Liu, Zhu (b13) 2012; 48 Gao, Zhou, Guan (b1) 2015; 323 Hwang, Yoon (b51) 2012 Kalousis, Prados, Hilario (b33) 2007; 12 Kou, Peng, Wang (b11) 2014; 275 Ferri, Hernández-Orallo, Modroiu (b24) 2009; 30 Neumayer, Mayer, Nørvåg (b30) 2011 Kou, Ergu, Shang (b40) 2014; 236 Sokolova, Lapalme (b23) 2009; 45 Almeida, Yamakami (b57) 2011 Liu, Dong, Liang, Chiclana, Herrera-Viedma (b63) 2018 Zavadskas, Turskis, Kildienė (b37) 2014; 20 T. Joachims, A probabilistic analysis of the rocchio algorithm with TFIDF for text categorization, in: International Conference on Machine Learning, 1996. Javed, Maruf, Babri (b28) 2015; 157 Kong, Owusu-Akomeah, Antwi (b4) 2019; 5 Nigam (10.1016/j.asoc.2019.105836_b49) 2000; 39 Stillwell (10.1016/j.asoc.2019.105836_b62) 1981; 28 Cortes (10.1016/j.asoc.2019.105836_b25) 2004 Neumayer (10.1016/j.asoc.2019.105836_b30) 2011 Junejo (10.1016/j.asoc.2019.105836_b2) 2016; 372 Sokolova (10.1016/j.asoc.2019.105836_b23) 2009; 45 Lee (10.1016/j.asoc.2019.105836_b16) 2006; 42 Singh (10.1016/j.asoc.2019.105836_b43) 2013; 5 Zavadskas (10.1016/j.asoc.2019.105836_b37) 2014; 20 Pinheiro (10.1016/j.asoc.2019.105836_b32) 2012; 39 Hwang (10.1016/j.asoc.2019.105836_b51) 2012 Kou (10.1016/j.asoc.2019.105836_b11) 2014; 275 Aghdam (10.1016/j.asoc.2019.105836_b29) 2009; 36 Mesterharm (10.1016/j.asoc.2019.105836_b56) 2011 Fazelabdolabadi (10.1016/j.asoc.2019.105836_b61) 2019; 5 Opricovic (10.1016/j.asoc.2019.105836_b52) 1998; 2 Peng (10.1016/j.asoc.2019.105836_b6) 2017; 418–419 Ogura (10.1016/j.asoc.2019.105836_b31) 2011; 38 Toloie-Eshlaghy (10.1016/j.asoc.2019.105836_b34) 2011 Chen (10.1016/j.asoc.2019.105836_b48) 2009; 36 Zhong (10.1016/j.asoc.2019.105836_b5) 2019; 5 Somol (10.1016/j.asoc.2019.105836_b9) 2010; 32 Shang (10.1016/j.asoc.2019.105836_b17) 2007; 33 Opricovic (10.1016/j.asoc.2019.105836_b53) 2010; 17 Peng (10.1016/j.asoc.2019.105836_b46) 2011; 11 Selvamuthu (10.1016/j.asoc.2019.105836_b59) 2019; 5 Zhang (10.1016/j.asoc.2019.105836_b36) 2019; 277 Kuo (10.1016/j.asoc.2019.105836_b12) 2008; 55 Yang (10.1016/j.asoc.2019.105836_b15) 1997 Li (10.1016/j.asoc.2019.105836_b35) 2016 Uysal (10.1016/j.asoc.2019.105836_b22) 2016; 43 Kong (10.1016/j.asoc.2019.105836_b4) 2019; 5 Yang (10.1016/j.asoc.2019.105836_b13) 2012; 48 Taşcı (10.1016/j.asoc.2019.105836_b14) 2013; 40 Gao (10.1016/j.asoc.2019.105836_b1) 2015; 323 Kou (10.1016/j.asoc.2019.105836_b47) 2012; 11 Zeng (10.1016/j.asoc.2019.105836_b8) 2015; 48 Ferri (10.1016/j.asoc.2019.105836_b24) 2009; 30 Liu (10.1016/j.asoc.2019.105836_b63) 2018 Sebastiani (10.1016/j.asoc.2019.105836_b3) 2001; 34 Davis (10.1016/j.asoc.2019.105836_b27) 2006 Kou (10.1016/j.asoc.2019.105836_b39) 2016; 22 Javed (10.1016/j.asoc.2019.105836_b28) 2015; 157 Maas (10.1016/j.asoc.2019.105836_b55) 2011 Shang (10.1016/j.asoc.2019.105836_b7) 2013; 54 Kalousis (10.1016/j.asoc.2019.105836_b33) 2007; 12 Pinheiro (10.1016/j.asoc.2019.105836_b21) 2015; 42 Song (10.1016/j.asoc.2019.105836_b60) 2018; 4 Kou (10.1016/j.asoc.2019.105836_b38) 2014; 235 Kou (10.1016/j.asoc.2019.105836_b40) 2014; 236 Almeida (10.1016/j.asoc.2019.105836_b57) 2011 Dernoncourt (10.1016/j.asoc.2019.105836_b10) 2014; 71 Uğuz (10.1016/j.asoc.2019.105836_b19) 2011; 24 Rehman (10.1016/j.asoc.2019.105836_b20) 2015; 42 Alias (10.1016/j.asoc.2019.105836_b44) 2008 Rosset (10.1016/j.asoc.2019.105836_b26) 2004 Liu (10.1016/j.asoc.2019.105836_b41) 2017; 36 Rokach (10.1016/j.asoc.2019.105836_b45) 2010; 33 Uysal (10.1016/j.asoc.2019.105836_b18) 2012; 36 10.1016/j.asoc.2019.105836_b58 10.1016/j.asoc.2019.105836_b54 10.1016/j.asoc.2019.105836_b50 Peng (10.1016/j.asoc.2019.105836_b42) 2011; 39 |
| References_xml | – start-page: 1 year: 2016 end-page: 11 ident: b35 article-title: A group decision making model for integrating heterogeneous information publication-title: IEEE Trans. Syst. Man Cybern. Syst. – volume: 38 start-page: 4978 year: 2011 end-page: 4989 ident: b31 article-title: Comparison of metrics for feature selection in imbalanced text classification publication-title: Expert Syst. Appl. – start-page: 850 year: 2011 end-page: 858 ident: b56 article-title: Active learning using on-line algorithms publication-title: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining – volume: 2 start-page: 5 year: 1998 end-page: 21 ident: b52 article-title: Multicriteria optimization of civil engineering systems publication-title: Fac. Civ. Eng. – volume: 5 start-page: 16 year: 2019 ident: b59 article-title: Indian stock market prediction using artificial neural networks on tick data publication-title: Financial Innov. – volume: 36 start-page: 5432 year: 2009 end-page: 5435 ident: b48 article-title: Feature selection for text classification with Naïve Bayes publication-title: Expert Syst. Appl. – volume: 372 start-page: 518 year: 2016 end-page: 538 ident: b2 article-title: Terms-based discriminative information space for robust text classification publication-title: Inform. Sci. – volume: 39 start-page: 677 year: 2011 end-page: 689 ident: b42 article-title: FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms publication-title: Omega – start-page: 313 year: 2004 end-page: 320 ident: b25 article-title: AUC optimization vs. error rate minimization publication-title: Adv. Neural Inf. Process. Syst. – volume: 36 start-page: 226 year: 2012 end-page: 235 ident: b18 article-title: A novel probabilistic feature selection method for text classification publication-title: Knowl.-Based Syst. – volume: 32 start-page: 1921 year: 2010 end-page: 1939 ident: b9 article-title: Evaluating stability and comparing output of feature selectors that optimize feature subset cardinality publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 33 start-page: 1 year: 2007 end-page: 5 ident: b17 article-title: A novel feature selection algorithm for text categorization publication-title: Expert Syst. Appl. – volume: 235 start-page: 225 year: 2014 end-page: 232 ident: b38 article-title: A cosine maximization method for the priority vector derivation in AHP publication-title: European J. Oper. Res. – volume: 323 start-page: 130 year: 2015 end-page: 142 ident: b1 article-title: Effectively classifying short texts by structured sparse representation with dictionary filtering publication-title: Inform. Sci. – volume: 236 start-page: 261 year: 2014 end-page: 271 ident: b40 article-title: Enhancing data consistency in decision matrix: Adapting hadamard model to mitigate judgment contradiction publication-title: European J. Oper. Res. – volume: 20 start-page: 165 year: 2014 end-page: 179 ident: b37 article-title: State of art surveys of overviews on MCDM/madm methods publication-title: Technol. Econ. Dev. Econ. – volume: 48 start-page: 741 year: 2012 end-page: 754 ident: b13 article-title: A new feature selection based on comprehensive measurement both in inter-category and intra-category for text categorization publication-title: Inf. Process. Manage. Int. J. – year: 2008 ident: b44 article-title: Multi crteria decision making and its applications : A literature review publication-title: Jurnal Teknologi Maklumat – start-page: 412 year: 1997 end-page: 420 ident: b15 article-title: A comparative study on feature selection in text categorization publication-title: Fourteenth International Conference on Machine Learning – volume: 55 start-page: 80 year: 2008 end-page: 93 ident: b12 article-title: The use of grey relational analysis in solving multiple attribute decision-making problems publication-title: Comput. Ind. Eng. – reference: T. Joachims, A probabilistic analysis of the rocchio algorithm with TFIDF for text categorization, in: International Conference on Machine Learning, 1996. – start-page: 86 year: 2011 end-page: 137 ident: b34 article-title: MCDM methodologies and applications: A literature review from 1999 to 2009 publication-title: Res.J. Int. Stud. – start-page: 763 year: 2011 end-page: 766 ident: b30 article-title: Combination of feature selection methods for text categorisation publication-title: Advances in Information Retrieval – volume: 36 start-page: 149 year: 2017 end-page: 161 ident: b41 article-title: Ranking products through online reviews: A method based on sentiment analysis technique and intuitionistic fuzzy set theory publication-title: Inf. Fusion – reference: Y. Saeys, T. Abeel, Y.V.D. Peer, Robust feature selection using ensemble feature selection techniques, in: Machine Learning and Knowledge Discovery in Databases, European Conference, Ecml/pkdd 2008, Antwerp, Belgium, September (2008) 15-19, Proceedings, DBLP, 2008, pp. 313–325. – start-page: 1 year: 2018 end-page: 12 ident: b63 article-title: Multiple attribute strategic weight manipulation with minimum cost in a group decision making context with interval attribute weights information publication-title: IEEE Trans. Syst. Man Cybern. Syst. – volume: 11 start-page: 2906 year: 2011 end-page: 2915 ident: b46 article-title: An empirical study of classification algorithm evaluation for financial risk prediction publication-title: Appl. Soft Comput. – volume: 157 start-page: 91 year: 2015 end-page: 104 ident: b28 article-title: A two-stage Markov blanket based feature selection algorithm for text classification publication-title: Neurocomputing – volume: 30 start-page: 27 year: 2009 end-page: 38 ident: b24 article-title: An experimental comparison of performance measures for classification publication-title: Pattern Recognit. Lett. – volume: 42 start-page: 155 year: 2006 end-page: 165 ident: b16 article-title: Information gain and divergence-based feature selection for machine learning-based text categorization publication-title: Inf. Process. Manage. – volume: 24 start-page: 1024 year: 2011 end-page: 1032 ident: b19 article-title: A two-stage feature selection method for text categorization by using information gain, principal component analysis and genetic algorithm publication-title: Knowl.-Based Syst. – volume: 5 start-page: 30 year: 2019 ident: b61 article-title: A hybrid Bayesian-network proposition for forecasting the crude oil price publication-title: Financial Innov. – start-page: 259 year: 2011 end-page: 262 ident: b57 article-title: Contributions to the study of SMS spam filtering: New collection and results publication-title: Proceedings of the 11th ACM Symposium on Document Engineering – volume: 4 start-page: 2 year: 2018 ident: b60 article-title: Sustainable strategy for corporate governance based on the sentiment analysis of financial reports with CSR publication-title: Financial Innov. – volume: 5 start-page: 10 year: 2019 ident: b4 article-title: Evaluation of the robusticity of mutual fund performance in ghana using enhanced resilient backpropagation neural network (ERBPNN) and fast adaptive neural network classifier (FANNC) publication-title: Financial Innov. – volume: 71 start-page: 681 year: 2014 end-page: 693 ident: b10 article-title: Analysis of feature selection stability on high dimension and small sample data publication-title: Comput. Statist. Data Anal. – volume: 33 start-page: 1 year: 2010 end-page: 39 ident: b45 article-title: Ensemble-based classifiers publication-title: Artif. Intell. Rev. – volume: 42 start-page: 3670 year: 2015 end-page: 3681 ident: b20 article-title: Relative discrimination criterion – A novel feature ranking method for text data publication-title: Expert Syst. Appl. – start-page: 233 year: 2006 end-page: 240 ident: b27 article-title: The relationship between precision-recall and ROC curves publication-title: ICML ’06 : Proceedings of the, International Conference on Machine Learning – volume: 12 start-page: 95 year: 2007 end-page: 116 ident: b33 article-title: Stability of feature selection algorithms: A study on high-dimensional spaces publication-title: Knowledge & Information Systems – year: 2012 ident: b51 article-title: Multiple Attribute Decision Making: Methods and Applications a State-of-the-Art Survey – volume: 39 start-page: 12851 year: 2012 end-page: 12857 ident: b32 article-title: A global-ranking local feature selection method for text categorization publication-title: Expert Syst. Appl. – volume: 34 start-page: 1 year: 2001 end-page: 47 ident: b3 article-title: Machine learning in automated text categorization publication-title: Acm Comput. Surv. – volume: 45 start-page: 427 year: 2009 end-page: 437 ident: b23 article-title: A systematic analysis of performance measures for classification tasks publication-title: Inf. Process. Manage. – reference: P. Bo, L. Lee, Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales (2005), pp. 115–124. – volume: 36 start-page: 6843 year: 2009 end-page: 6853 ident: b29 article-title: Text feature selection using ant colony optimization publication-title: Expert Syst. Appl. – start-page: 142 year: 2011 end-page: 150 ident: b55 article-title: Learning word vectors for sentiment analysis publication-title: Meeting of the Association for Computational Linguistics: Human Language Technologies – volume: 17 start-page: 211 year: 2010 end-page: 220 ident: b53 article-title: Multicriteria planning of post earthquake sustainable reconstruction publication-title: Comput.-Aided Civ. Infrastruct. Eng. – volume: 40 start-page: 4871 year: 2013 end-page: 4886 ident: b14 article-title: Comparison of text feature selection policies and using an adaptive framework publication-title: Expert Syst. Appl. – volume: 11 start-page: 197 year: 2012 end-page: 225 ident: b47 article-title: Evaluation of classification algorithms using mcdm and rank correlation publication-title: Int. J. Inf. Technol. Decis. Mak. – volume: 39 start-page: 103 year: 2000 end-page: 134 ident: b49 article-title: Text classification from labeled and unlabeled documents using EM publication-title: Mach. Learn. – volume: 418–419 start-page: 652 year: 2017 end-page: 667 ident: b6 article-title: Feature selection by optimizing a lower bound of conditional mutual information publication-title: Inform. Sci. – volume: 277 start-page: 964 year: 2019 end-page: 980 ident: b36 article-title: Soft consensus cost models for group decision making and economic interpretations publication-title: European J. Oper. Res. – start-page: 89 year: 2004 ident: b26 article-title: Model selection via the AUC publication-title: International Conference on Machine Learning – volume: 28 start-page: 62 year: 1981 end-page: 77 ident: b62 article-title: A comparison of weight approximation techniques in multiattribute utility decision making publication-title: Organ. Behav. Hum. Perform. – volume: 275 start-page: 1 year: 2014 end-page: 12 ident: b11 article-title: Evaluation of clustering algorithms for financial risk analysis using MCDM methods publication-title: Inform. Sci. – volume: 5 start-page: 4598 year: 2013 end-page: 4604 ident: b43 article-title: TOPSIS based multi-criteria decision making of feature selection techniques for network traffic dataset publication-title: Int. J. Eng. Technol. – volume: 42 start-page: 1941 year: 2015 end-page: 1949 ident: b21 article-title: Data-driven global-ranking local feature selection methods for text categorization publication-title: Expert Syst. Appl. – volume: 48 start-page: 2656 year: 2015 end-page: 2666 ident: b8 article-title: A novel feature selection method considering feature interaction publication-title: Pattern Recognit. – volume: 43 start-page: 82 year: 2016 end-page: 92 ident: b22 article-title: An improved global feature selection scheme for text classification publication-title: Expert Syst. Appl. – volume: 5 start-page: 4 year: 2019 ident: b5 article-title: Predicting the daily return direction of the stock market using hybrid machine learning algorithms publication-title: Financial Innov. – volume: 22 start-page: 738 year: 2016 end-page: 765 ident: b39 article-title: Pairwise comparison matrix in multiple criteria decision making publication-title: Technol. Econ. Develop. Econ. – volume: 54 start-page: 298 year: 2013 end-page: 309 ident: b7 article-title: Feature selection via maximizing global information gain for text classification publication-title: Knowl.-Based Syst. – volume: 418–419 start-page: 652 year: 2017 ident: 10.1016/j.asoc.2019.105836_b6 article-title: Feature selection by optimizing a lower bound of conditional mutual information publication-title: Inform. Sci. doi: 10.1016/j.ins.2017.08.036 – volume: 28 start-page: 62 issue: 1 year: 1981 ident: 10.1016/j.asoc.2019.105836_b62 article-title: A comparison of weight approximation techniques in multiattribute utility decision making publication-title: Organ. Behav. Hum. Perform. doi: 10.1016/0030-5073(81)90015-5 – volume: 42 start-page: 1941 issue: 4 year: 2015 ident: 10.1016/j.asoc.2019.105836_b21 article-title: Data-driven global-ranking local feature selection methods for text categorization publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2014.10.011 – start-page: 1 year: 2018 ident: 10.1016/j.asoc.2019.105836_b63 article-title: Multiple attribute strategic weight manipulation with minimum cost in a group decision making context with interval attribute weights information publication-title: IEEE Trans. Syst. Man Cybern. Syst. doi: 10.1109/TSMC.2018.2841063 – volume: 5 start-page: 4 issue: 1 year: 2019 ident: 10.1016/j.asoc.2019.105836_b5 article-title: Predicting the daily return direction of the stock market using hybrid machine learning algorithms publication-title: Financial Innov. doi: 10.1186/s40854-019-0138-0 – volume: 33 start-page: 1 issue: 1–2 year: 2010 ident: 10.1016/j.asoc.2019.105836_b45 article-title: Ensemble-based classifiers publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-009-9124-7 – start-page: 89 year: 2004 ident: 10.1016/j.asoc.2019.105836_b26 article-title: Model selection via the AUC – volume: 38 start-page: 4978 issue: 5 year: 2011 ident: 10.1016/j.asoc.2019.105836_b31 article-title: Comparison of metrics for feature selection in imbalanced text classification publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2010.09.153 – volume: 275 start-page: 1 issue: 11 year: 2014 ident: 10.1016/j.asoc.2019.105836_b11 article-title: Evaluation of clustering algorithms for financial risk analysis using MCDM methods publication-title: Inform. Sci. doi: 10.1016/j.ins.2014.02.137 – volume: 48 start-page: 741 issue: 4 year: 2012 ident: 10.1016/j.asoc.2019.105836_b13 article-title: A new feature selection based on comprehensive measurement both in inter-category and intra-category for text categorization publication-title: Inf. Process. Manage. Int. J. doi: 10.1016/j.ipm.2011.12.005 – volume: 42 start-page: 155 issue: 1 year: 2006 ident: 10.1016/j.asoc.2019.105836_b16 article-title: Information gain and divergence-based feature selection for machine learning-based text categorization publication-title: Inf. Process. Manage. doi: 10.1016/j.ipm.2004.08.006 – year: 2012 ident: 10.1016/j.asoc.2019.105836_b51 – volume: 30 start-page: 27 issue: 1 year: 2009 ident: 10.1016/j.asoc.2019.105836_b24 article-title: An experimental comparison of performance measures for classification publication-title: Pattern Recognit. Lett. doi: 10.1016/j.patrec.2008.08.010 – volume: 20 start-page: 165 issue: 1 year: 2014 ident: 10.1016/j.asoc.2019.105836_b37 article-title: State of art surveys of overviews on MCDM/madm methods publication-title: Technol. Econ. Dev. Econ. doi: 10.3846/20294913.2014.892037 – volume: 11 start-page: 2906 issue: 2 year: 2011 ident: 10.1016/j.asoc.2019.105836_b46 article-title: An empirical study of classification algorithm evaluation for financial risk prediction publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2010.11.028 – volume: 39 start-page: 103 issue: 2–3 year: 2000 ident: 10.1016/j.asoc.2019.105836_b49 article-title: Text classification from labeled and unlabeled documents using EM publication-title: Mach. Learn. doi: 10.1023/A:1007692713085 – volume: 36 start-page: 6843 issue: 3 year: 2009 ident: 10.1016/j.asoc.2019.105836_b29 article-title: Text feature selection using ant colony optimization publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2008.08.022 – start-page: 850 year: 2011 ident: 10.1016/j.asoc.2019.105836_b56 article-title: Active learning using on-line algorithms – volume: 372 start-page: 518 year: 2016 ident: 10.1016/j.asoc.2019.105836_b2 article-title: Terms-based discriminative information space for robust text classification publication-title: Inform. Sci. doi: 10.1016/j.ins.2016.08.073 – volume: 5 start-page: 16 issue: 1 year: 2019 ident: 10.1016/j.asoc.2019.105836_b59 article-title: Indian stock market prediction using artificial neural networks on tick data publication-title: Financial Innov. doi: 10.1186/s40854-019-0131-7 – volume: 42 start-page: 3670 issue: 7 year: 2015 ident: 10.1016/j.asoc.2019.105836_b20 article-title: Relative discrimination criterion – A novel feature ranking method for text data publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2014.12.013 – volume: 43 start-page: 82 issue: C year: 2016 ident: 10.1016/j.asoc.2019.105836_b22 article-title: An improved global feature selection scheme for text classification publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2015.08.050 – volume: 39 start-page: 12851 issue: 17 year: 2012 ident: 10.1016/j.asoc.2019.105836_b32 article-title: A global-ranking local feature selection method for text categorization publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2012.05.008 – volume: 11 start-page: 197 issue: 01 year: 2012 ident: 10.1016/j.asoc.2019.105836_b47 article-title: Evaluation of classification algorithms using mcdm and rank correlation publication-title: Int. J. Inf. Technol. Decis. Mak. doi: 10.1142/S0219622012500095 – volume: 22 start-page: 738 issue: 5 year: 2016 ident: 10.1016/j.asoc.2019.105836_b39 article-title: Pairwise comparison matrix in multiple criteria decision making publication-title: Technol. Econ. Develop. Econ. doi: 10.3846/20294913.2016.1210694 – start-page: 142 year: 2011 ident: 10.1016/j.asoc.2019.105836_b55 article-title: Learning word vectors for sentiment analysis – volume: 71 start-page: 681 issue: 1 year: 2014 ident: 10.1016/j.asoc.2019.105836_b10 article-title: Analysis of feature selection stability on high dimension and small sample data publication-title: Comput. Statist. Data Anal. doi: 10.1016/j.csda.2013.07.012 – start-page: 1 year: 2016 ident: 10.1016/j.asoc.2019.105836_b35 article-title: A group decision making model for integrating heterogeneous information publication-title: IEEE Trans. Syst. Man Cybern. Syst. doi: 10.1109/TSMC.2015.2422267 – start-page: 763 year: 2011 ident: 10.1016/j.asoc.2019.105836_b30 article-title: Combination of feature selection methods for text categorisation – volume: 48 start-page: 2656 issue: 8 year: 2015 ident: 10.1016/j.asoc.2019.105836_b8 article-title: A novel feature selection method considering feature interaction publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.02.025 – volume: 5 start-page: 10 issue: 1 year: 2019 ident: 10.1016/j.asoc.2019.105836_b4 article-title: Evaluation of the robusticity of mutual fund performance in ghana using enhanced resilient backpropagation neural network (ERBPNN) and fast adaptive neural network classifier (FANNC) publication-title: Financial Innov. doi: 10.1186/s40854-019-0125-5 – volume: 157 start-page: 91 year: 2015 ident: 10.1016/j.asoc.2019.105836_b28 article-title: A two-stage Markov blanket based feature selection algorithm for text classification publication-title: Neurocomputing doi: 10.1016/j.neucom.2015.01.031 – volume: 4 start-page: 2 issue: 1 year: 2018 ident: 10.1016/j.asoc.2019.105836_b60 article-title: Sustainable strategy for corporate governance based on the sentiment analysis of financial reports with CSR publication-title: Financial Innov. doi: 10.1186/s40854-018-0086-0 – volume: 36 start-page: 226 issue: 6 year: 2012 ident: 10.1016/j.asoc.2019.105836_b18 article-title: A novel probabilistic feature selection method for text classification publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2012.06.005 – year: 2008 ident: 10.1016/j.asoc.2019.105836_b44 article-title: Multi crteria decision making and its applications : A literature review publication-title: Jurnal Teknologi Maklumat – volume: 34 start-page: 1 issue: 1 year: 2001 ident: 10.1016/j.asoc.2019.105836_b3 article-title: Machine learning in automated text categorization publication-title: Acm Comput. Surv. doi: 10.1145/505282.505283 – start-page: 259 year: 2011 ident: 10.1016/j.asoc.2019.105836_b57 article-title: Contributions to the study of SMS spam filtering: New collection and results – volume: 45 start-page: 427 issue: 4 year: 2009 ident: 10.1016/j.asoc.2019.105836_b23 article-title: A systematic analysis of performance measures for classification tasks publication-title: Inf. Process. Manage. doi: 10.1016/j.ipm.2009.03.002 – volume: 277 start-page: 964 issue: 3 year: 2019 ident: 10.1016/j.asoc.2019.105836_b36 article-title: Soft consensus cost models for group decision making and economic interpretations publication-title: European J. Oper. Res. doi: 10.1016/j.ejor.2019.03.009 – volume: 236 start-page: 261 issue: 1 year: 2014 ident: 10.1016/j.asoc.2019.105836_b40 article-title: Enhancing data consistency in decision matrix: Adapting hadamard model to mitigate judgment contradiction publication-title: European J. Oper. Res. doi: 10.1016/j.ejor.2013.11.035 – start-page: 412 year: 1997 ident: 10.1016/j.asoc.2019.105836_b15 article-title: A comparative study on feature selection in text categorization – volume: 36 start-page: 5432 issue: 3 year: 2009 ident: 10.1016/j.asoc.2019.105836_b48 article-title: Feature selection for text classification with Naïve Bayes publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2008.06.054 – volume: 5 start-page: 30 issue: 1 year: 2019 ident: 10.1016/j.asoc.2019.105836_b61 article-title: A hybrid Bayesian-network proposition for forecasting the crude oil price publication-title: Financial Innov. doi: 10.1186/s40854-019-0144-2 – start-page: 313 year: 2004 ident: 10.1016/j.asoc.2019.105836_b25 article-title: AUC optimization vs. error rate minimization publication-title: Adv. Neural Inf. Process. Syst. – ident: 10.1016/j.asoc.2019.105836_b54 – volume: 32 start-page: 1921 issue: 11 year: 2010 ident: 10.1016/j.asoc.2019.105836_b9 article-title: Evaluating stability and comparing output of feature selectors that optimize feature subset cardinality publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2010.34 – volume: 39 start-page: 677 issue: 6 year: 2011 ident: 10.1016/j.asoc.2019.105836_b42 article-title: FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms publication-title: Omega doi: 10.1016/j.omega.2011.01.009 – ident: 10.1016/j.asoc.2019.105836_b58 – volume: 2 start-page: 5 issue: 1 year: 1998 ident: 10.1016/j.asoc.2019.105836_b52 article-title: Multicriteria optimization of civil engineering systems publication-title: Fac. Civ. Eng. – ident: 10.1016/j.asoc.2019.105836_b50 – volume: 323 start-page: 130 year: 2015 ident: 10.1016/j.asoc.2019.105836_b1 article-title: Effectively classifying short texts by structured sparse representation with dictionary filtering publication-title: Inform. Sci. doi: 10.1016/j.ins.2015.06.033 – volume: 55 start-page: 80 issue: 1 year: 2008 ident: 10.1016/j.asoc.2019.105836_b12 article-title: The use of grey relational analysis in solving multiple attribute decision-making problems publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2007.12.002 – volume: 33 start-page: 1 issue: 1 year: 2007 ident: 10.1016/j.asoc.2019.105836_b17 article-title: A novel feature selection algorithm for text categorization publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2006.04.001 – start-page: 233 year: 2006 ident: 10.1016/j.asoc.2019.105836_b27 article-title: The relationship between precision-recall and ROC curves – volume: 54 start-page: 298 issue: 4 year: 2013 ident: 10.1016/j.asoc.2019.105836_b7 article-title: Feature selection via maximizing global information gain for text classification publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2013.09.019 – volume: 24 start-page: 1024 issue: 7 year: 2011 ident: 10.1016/j.asoc.2019.105836_b19 article-title: A two-stage feature selection method for text categorization by using information gain, principal component analysis and genetic algorithm publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2011.04.014 – volume: 235 start-page: 225 issue: 1 year: 2014 ident: 10.1016/j.asoc.2019.105836_b38 article-title: A cosine maximization method for the priority vector derivation in AHP publication-title: European J. Oper. Res. doi: 10.1016/j.ejor.2013.10.019 – volume: 5 start-page: 4598 issue: 6 year: 2013 ident: 10.1016/j.asoc.2019.105836_b43 article-title: TOPSIS based multi-criteria decision making of feature selection techniques for network traffic dataset publication-title: Int. J. Eng. Technol. – volume: 40 start-page: 4871 issue: 12 year: 2013 ident: 10.1016/j.asoc.2019.105836_b14 article-title: Comparison of text feature selection policies and using an adaptive framework publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2013.02.019 – volume: 17 start-page: 211 issue: 3 year: 2010 ident: 10.1016/j.asoc.2019.105836_b53 article-title: Multicriteria planning of post earthquake sustainable reconstruction publication-title: Comput.-Aided Civ. Infrastruct. Eng. doi: 10.1111/1467-8667.00269 – start-page: 86 year: 2011 ident: 10.1016/j.asoc.2019.105836_b34 article-title: MCDM methodologies and applications: A literature review from 1999 to 2009 publication-title: Res.J. Int. Stud. – volume: 12 start-page: 95 issue: 1 year: 2007 ident: 10.1016/j.asoc.2019.105836_b33 article-title: Stability of feature selection algorithms: A study on high-dimensional spaces publication-title: Knowledge & Information Systems doi: 10.1007/s10115-006-0040-8 – volume: 36 start-page: 149 year: 2017 ident: 10.1016/j.asoc.2019.105836_b41 article-title: Ranking products through online reviews: A method based on sentiment analysis technique and intuitionistic fuzzy set theory publication-title: Inf. Fusion doi: 10.1016/j.inffus.2016.11.012 |
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