Model Explanation and Interpretation Concepts for Stimulating Advanced Human-Machine Interaction with "Expert-in-the-Loop"
暂无分享,去创建一个
[1] Enrique Castillo,et al. Expert Systems: Uncertainty and Learning , 1991 .
[2] Xiao-Jun Zeng,et al. An improved approach of self-organising fuzzy neural network based on similarity measures , 2012, Evol. Syst..
[3] Jesús S. Aguilar-Ruiz,et al. Knowledge discovery from data streams , 2009, Intell. Data Anal..
[4] Edwin Lughofer,et al. Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications , 2011, Studies in Fuzziness and Soft Computing.
[5] John Q. Gan,et al. Low-level interpretability and high-level interpretability: a unified view of data-driven interpretable fuzzy system modelling , 2008, Fuzzy Sets Syst..
[6] Majid Nili Ahmadabadi,et al. Online Local Input Selection Through Evolving Heterogeneous Fuzzy Inference System , 2016, IEEE Transactions on Fuzzy Systems.
[7] Walmir M. Caminhas,et al. Adaptive fault detection and diagnosis using an evolving fuzzy classifier , 2013, Inf. Sci..
[8] Edwin Lughofer,et al. Learning in Non-Stationary Environments: Methods and Applications , 2012 .
[9] Edwin Lughofer,et al. Towards incremental classifier fusion , 2010, Intell. Data Anal..
[10] Antonio Fiordaliso,et al. A constrained Takagi-Sugeno fuzzy system that allows for better interpretation and analysis , 2001, Fuzzy Sets Syst..
[11] Namchul Do,et al. A predictive maintenance approach based on real-time internal parameter monitoring , 2016 .
[12] Christian Brecher,et al. Self-optimizing Production Systems☆ , 2016 .
[13] Sreenatha G. Anavatti,et al. Evolving type-2 web news mining , 2017, Appl. Soft Comput..
[14] José M. Alonso,et al. Special issue on interpretable fuzzy systems , 2011, Inf. Sci..
[15] Petr Hájek,et al. Metamathematics of Fuzzy Logic , 1998, Trends in Logic.
[16] Martin Burger,et al. Regularized data-driven construction of fuzzy controllers , 2002 .
[17] Daniela Fogli,et al. Visual Interactive Systems for End-User Development: A Model-Based Design Methodology , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.
[18] Eyke Hüllermeier,et al. Visualization of evolving fuzzy rule-based systems , 2014, Evol. Syst..
[19] Motoaki Kawanabe,et al. How to Explain Individual Classification Decisions , 2009, J. Mach. Learn. Res..
[20] Lotfi A. Zadeh,et al. Fuzzy Sets , 1996, Inf. Control..
[21] Edwin Lughofer,et al. On-line assurance of interpretability criteria in evolving fuzzy systems - Achievements, new concepts and open issues , 2013, Inf. Sci..
[22] Witold Pedrycz,et al. Fuzzy Systems Engineering , 2007 .
[23] Erik Strumbelj,et al. Explaining prediction models and individual predictions with feature contributions , 2014, Knowledge and Information Systems.
[24] Hisao Ishibuchi,et al. A weighted fuzzy classifier and its application to image processing tasks , 2007, Fuzzy Sets Syst..
[25] E. Lughofer,et al. Evolving fuzzy classifiers using different model architectures , 2008, Fuzzy Sets Syst..
[26] Witold Pedrycz,et al. Fuzzy Systems Engineering - Toward Human-Centric Computing , 2007 .
[27] Mahardhika Pratama,et al. Top–Down Sparse Fuzzy Regression Modeling from Data with Improved Coverage , 2017, Int. J. Fuzzy Syst..
[28] Giovanna Castellano,et al. Distinguishability quantification of fuzzy sets , 2007, Inf. Sci..
[29] Simone Santini,et al. Similarity Measures , 1999, IEEE Trans. Pattern Anal. Mach. Intell..
[30] Paramasivan Saratchandran,et al. Sequential Adaptive Fuzzy Inference System (SAFIS) for nonlinear system identification and prediction , 2006, Fuzzy Sets Syst..
[31] Edwin Lughofer,et al. On-line incremental feature weighting in evolving fuzzy classifiers , 2011, Fuzzy Sets Syst..
[32] Subhash C. Bagui,et al. Combining Pattern Classifiers: Methods and Algorithms , 2005, Technometrics.
[33] Eyke Hüllermeier,et al. Top-Down Induction of Fuzzy Pattern Trees , 2011, IEEE Transactions on Fuzzy Systems.
[34] Pengcheng Shi,et al. An Expert-in-the-loop Paradigm for Learning Medical Image Grouping , 2016, PAKDD.
[35] Lefteri H. Tsoukalas,et al. Fuzzy and neural approaches in engineering , 1997 .
[36] Fuchun Sun,et al. Hierarchical Structured Sparse Representation for T–S Fuzzy Systems Identification , 2013, IEEE Transactions on Fuzzy Systems.
[37] Hisao Ishibuchi,et al. Effect of rule weights in fuzzy rule-based classification systems , 2001, IEEE Trans. Fuzzy Syst..
[38] Plamen Angelov,et al. Autonomous Learning Systems: From Data Streams to Knowledge in Real-time , 2013 .
[39] Andrzej Piegat,et al. Fuzzy Modeling and Control , 2001 .
[40] Ahmad T. Al-Taani. An Expert System for Car Failure Diagnosis , 2005, IEC.
[41] Plamen P. Angelov,et al. Fully unsupervised fault detection and identification based on recursive density estimation and self-evolving cloud-based classifier , 2015, Neurocomputing.
[42] Yaochu Jin,et al. Advanced fuzzy systems design and applications , 2003, Studies in Fuzziness and Soft Computing.
[43] Jianghai Hu,et al. Local Model Predictive Control for T–S Fuzzy Systems , 2017, IEEE Transactions on Cybernetics.
[44] Wei-Yin Loh,et al. Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..
[45] Michio Sugeno,et al. Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.
[46] Henry L. Owen,et al. Towards self-healing systems: re-establishing trust in compromised systems , 2006 .
[47] Andreas Holzinger,et al. Interactive machine learning for health informatics: when do we need the human-in-the-loop? , 2016, Brain Informatics.
[48] Edwin Lughofer,et al. Associating visual textures with human perceptions using genetic algorithms , 2010, Inf. Sci..
[49] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[50] Alex Arenas,et al. Neural virtual sensor for the inferential prediction of product quality from process variables , 2002 .
[51] Ludmila I. Kuncheva,et al. Fuzzy Classifier Design , 2000, Studies in Fuzziness and Soft Computing.
[52] Chuen-Chien Lee. FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .
[53] Eyke Hüllermeier,et al. FR3: A Fuzzy Rule Learner for Inducing Reliable Classifiers , 2009, IEEE Transactions on Fuzzy Systems.
[54] Jonas Sjöberg,et al. Efficient training of neural nets for nonlinear adaptive filtering using a recursive Levenberg-Marquardt algorithm , 2000, IEEE Trans. Signal Process..
[55] Antonio Fiordaliso. Autostructuration of fuzzy systems by rules sensitivity analysis , 2001, Fuzzy Sets Syst..
[56] J. Casillas. Interpretability issues in fuzzy modeling , 2003 .
[57] Susanne Saminger-Platz,et al. Detecting clipping in photovoltaic solar plants using fuzzy systems on the feature space , 2016 .
[58] Jerome H. Friedman,et al. Diagnostics and extrapolation in machine learning , 2004 .
[59] Plamen P. Angelov,et al. Simpl_eTS: a simplified method for learning evolving Takagi-Sugeno fuzzy models , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..
[60] O. Nelles. Nonlinear System Identification , 2001 .
[61] Magne Setnes. Simplification and reduction of fuzzy rules , 2003 .
[62] Scott Lundberg,et al. An unexpected unity among methods for interpreting model predictions , 2016, ArXiv.
[63] Edwin Lughofer,et al. Single-pass active learning with conflict and ignorance , 2012, Evolving Systems.
[64] Edwin Lughofer,et al. Machine learning based analysis of gender differences in visual inspection decision making , 2013, Inf. Sci..
[65] Edwin Lughofer,et al. On-line elimination of local redundancies in evolving fuzzy systems , 2011, Evol. Syst..
[66] Edwin Lughofer,et al. On employing fuzzy modeling algorithms for the valuation of residential premises , 2011, Inf. Sci..
[67] Edwin Lughofer,et al. Integrating new classes on the fly in evolving fuzzy classifier designs and their application in visual inspection , 2015, Appl. Soft Comput..
[68] R. Polikar,et al. Ensemble based systems in decision making , 2006, IEEE Circuits and Systems Magazine.
[69] Ian H. Witten,et al. Chapter 15 – Embedded Machine Learning , 2011 .
[70] Plamen P. Angelov,et al. Creating Evolving User Behavior Profiles Automatically , 2012, IEEE Transactions on Knowledge and Data Engineering.
[71] Bart Baesens,et al. An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models , 2011, Decis. Support Syst..
[72] Praminda Caleb-Solly,et al. Adaptive surface inspection via interactive evolution , 2007, Image Vis. Comput..
[73] Edwin Lughofer,et al. On-Line Fault Detection with Data-Driven Evolving Fuzzy Models , 2008, Control. Intell. Syst..
[74] Edwin Lughofer,et al. Flexible Evolving Fuzzy Inference Systems from Data Streams (FLEXFIS , 2012 .
[75] Plamen P. Angelov,et al. Evolving classification of agents’ behaviors: a general approach , 2010, Evol. Syst..
[76] V. Cross,et al. Similarity and Compatibility in Fuzzy Set Theory: Assessment And Applications , 2010 .
[77] Nikola K. Kasabov,et al. Incremental linear discriminant analysis for evolving feature spaces in multitask pattern recognition problems , 2010, Evol. Syst..
[78] John B. Wong,et al. Decision making in health and medicine: Integrating evidence and values, second edition , 2014 .
[79] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[80] Yang Liu,et al. Predictive Modeling for Intelligent Maintenance in Complex Semiconductor Manufacturing Processes. , 2008 .
[81] Ian H. Witten,et al. Interactive machine learning: letting users build classifiers , 2002, Int. J. Hum. Comput. Stud..
[82] Edwin Lughofer,et al. Advanced linguistic explanations of classifier decisions for users' annotation support , 2016, 2016 IEEE 8th International Conference on Intelligent Systems (IS).
[83] B. Kosko. Fuzzy Thinking: The New Science of Fuzzy Logic , 1993 .
[84] János Abonyi,et al. Fuzzy Model Identification for Control , 2003 .
[85] Eyke Hüllermeier,et al. Learning valued preference structures for solving classification problems , 2008, Fuzzy Sets Syst..
[86] Ronald R. Yager,et al. On the construction of hierarchical fuzzy systems models , 1998, IEEE Trans. Syst. Man Cybern. Part C.
[87] Plamen Angelov,et al. Evolving Takagi‐Sugeno Fuzzy Systems from Streaming Data (eTS+) , 2010 .
[88] Jian-Bo Yang,et al. Development of a fuzzy FMEA based product design system , 2008 .
[89] E. H. Mamdani,et al. Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis , 1976, IEEE Transactions on Computers.
[90] Karl-Friedrich Kraiss. Advanced Man-Machine Interaction: Fundamentals and Implementation (Signals and Communication Technology) , 2006 .
[91] Edwin Lughofer,et al. Multi-objective knowledge-based strategy for process parameter optimization in Micro-fluidic chip production , 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).
[92] Mohamed Medhat Gaber,et al. Knowledge discovery from data streams , 2009, IDA 2009.
[93] Ronald R. Yager,et al. A model of participatory learning , 1990, IEEE Trans. Syst. Man Cybern..
[94] Ludmila I. Kuncheva,et al. Combining Pattern Classifiers: Methods and Algorithms , 2004 .
[95] Neil M. White,et al. Intelligent sensors—a generic software approach , 2005 .
[96] Brian Mac Namee,et al. Active learning for text classification with reusability , 2016, Expert Syst. Appl..
[97] J. Hibbard,et al. Supporting Patient Behavior Change: Approaches Used by Primary Care Clinicians Whose Patients Have an Increase in Activation Levels , 2016, The Annals of Family Medicine.
[98] W. Wang,et al. An Evolving Fuzzy Predictor for Industrial Applications , 2008, IEEE Transactions on Fuzzy Systems.
[99] Mahardhika Pratama,et al. Scaffolding type-2 classifier for incremental learning under concept drifts , 2016, Neurocomputing.
[100] Kevin A. Wise,et al. Robust Adaptive Control , 2013 .
[101] Edwin Lughofer,et al. Robust Data-Driven Fault Detection in Dynamic Process Environments Using Discrete Event Systems , 2018 .
[102] João Gama,et al. Enhancing data stream predictions with reliability estimators and explanation , 2014, Eng. Appl. Artif. Intell..
[103] Edwin Lughofer,et al. Self-adaptive evolving forecast models with incremental PLS space updating for on-line prediction of micro-fluidic chip quality , 2018, Eng. Appl. Artif. Intell..
[104] Edwin Lughofer,et al. Reliable All-Pairs Evolving Fuzzy Classifiers , 2013, IEEE Transactions on Fuzzy Systems.
[105] Plamen Angelov,et al. Evolving Intelligent Systems: Methodology and Applications , 2010 .
[106] Kevin A. Wise,et al. Robust and Adaptive Control , 2013 .
[107] Francesc Esteva,et al. Review of Triangular norms by E. P. Klement, R. Mesiar and E. Pap. Kluwer Academic Publishers , 2003 .
[108] Babak Nadjar Araabi,et al. An online predictor model as adaptive habitually linear and transiently nonlinear model , 2010, Evol. Syst..
[109] Igor Škrjanc,et al. Confidence interval of fuzzy models: An example using a waste-water treatment plant , 2009 .
[110] Thomas Vetterlein,et al. Vagueness: where degree-based approaches are useful, and where we can do without , 2012, Soft Computing.
[111] Edwin Lughofer,et al. Learning in Non-Stationary Environments , 2012 .
[112] Ian H. Witten,et al. Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .
[113] Mark Last,et al. Predictive Maintenance with Multi-target Classification Models , 2010, ACIIDS.
[114] Eyke Hüllermeier,et al. On-line Redundancy Elimination in Evolving Fuzzy Regression Models using a Fuzzy Inclusion Measure , 2011, EUSFLAT Conf..
[115] Peter Jackson,et al. Introduction to expert systems , 1986 .
[116] Joel Levitt,et al. Complete guide to predictive and predictive maintenance , 2003 .
[117] M. D. McKay,et al. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code , 2000 .
[118] Juan Luis Castro,et al. Fuzzy systems with defuzzification are universal approximators , 1996, IEEE Trans. Syst. Man Cybern. Part B.
[119] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[120] Khaled Ghédira,et al. Discussion and review on evolving data streams and concept drift adapting , 2018, Evol. Syst..
[121] Francisco Herrera,et al. Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures , 2011, Inf. Sci..
[122] Mahardhika Pratama,et al. Generalized smart evolving fuzzy systems , 2015, Evol. Syst..
[123] Eyke Hüllermeier,et al. Rule Chains for Visualizing Evolving Fuzzy Rule-Based Systems , 2013, CORES.
[124] Araceli Sanchis,et al. Online activity recognition using evolving classifiers , 2013, Expert Syst. Appl..
[125] Marko Robnik-Sikonja,et al. Explaining Classifications For Individual Instances , 2008, IEEE Transactions on Knowledge and Data Engineering.
[126] U. Rajendra Acharya,et al. Machine Learning in Healthcare Informatics , 2013, Machine Learning in Healthcare Informatics.
[127] Edwin Lughofer,et al. On improving performance of surface inspection systems by online active learning and flexible classifier updates , 2015, Machine Vision and Applications.
[128] Edwin Lughofer,et al. Human–Machine Interaction Issues in Quality Control Based on Online Image Classification , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.