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Application of fuzzy rule induction to data mining [chapter]

Christophe Marsala
1998 Lecture Notes in Computer Science  
doi:10.1007/bfb0056007 fatcat:u7ckkd2fobasjnk7dcnx56iyzu

Fuzzy Decision Tree Induction Approach for Mining Fuzzy Association Rules [chapter]

Rolly Intan, Oviliani Yenty Yuliana
2009 Lecture Notes in Computer Science  
In this paper, we extend the concept of DTI dealing with meaningful fuzzy labels in order to express human knowledge for mining fuzzy association rules.  ...  Decision Tree Induction (DTI), one of the Data Mining classification methods, is used in this research for predictive problem solving in analyzing patient medical track records.  ...  Mining Fuzzy Association Rules from FDT Association rules are kind of patterns representing correlation of attribute-value (items) in a given set of data provided by a process of data mining system.  ... 
doi:10.1007/978-3-642-10684-2_80 fatcat:nwck36br5jdufmrioavmuoblhy

Association Rule And Decision Tree Based Methodsfor Fuzzy Rule Base Generation

Ferenc Peter Pach, Janos Abonyi
2008 Zenodo  
This paper focuses on the data-driven generation of fuzzy IF...THEN rules.  ...  The resulted fuzzy rule base can be applied to build a classifier, a model used for prediction, or it can be applied to form a decision support system.  ...  FUZZY DECISION TREE BASED METHODS A. Existent decision tree induction algorithms Decision tree based methods are widely used in data mining and decision support applications.  ... 
doi:10.5281/zenodo.1082148 fatcat:ksus2wguovhenbv6vcyjgec2aa

Generalizations of Rough Sets: From Crisp to Fuzzy Cases [chapter]

Masahiro Inuiguchi
2004 Lecture Notes in Computer Science  
Inequalities p. 204 A Graded Applicability of Rules p. 213 On the Degree of Independence of a Contingency Matrix p. 219 K Nearest Neighbor Classification with Local Induction of the Simple Value  ...  . 586 Data Mining On the Evolution of Rough Set Exploration System p. 592 Discovering Maximal Frequent Patterns in Sequence Groups p. 602 Fuzzy Taxonomic, Quantitative Database and Mining Generalized  ... 
doi:10.1007/978-3-540-25929-9_3 fatcat:saiacsrpovgphlh5zzhoq4tcrq

Optimization of Decision Rules in Fuzzy Classification

Renuka Arora, Sudesh Kumar
2012 International Journal of Computer Applications  
Discovering knowledge in the form of classification rules is one of the most important tasks of data mining. Discovery of comprehensible, concise and effective rules helps us to make right decisions.  ...  Recently there have been several applications of genetic algorithms for effective rules with high predictive accuracy.  ...  KDD Process: The KDD process includes two steps: Preprocessing [or Data Preparation] step The goal of data preparation methods is to transform the data to facilitate the application of given data mining  ... 
doi:10.5120/8021-0505 fatcat:ginu6nhot5ajnghpclsmngbqbq

Fuzzy methods in machine learning and data mining: Status and prospects

Eyke Hüllermeier
2005 Fuzzy sets and systems (Print)  
This paper briefly reviews some typical applications and highlights potential contributions that fuzzy set theory can make to machine learning, data mining, and related fields.  ...  Over the past years, methods for the automated induction of models and the extraction of interesting patterns from empirical data have attracted considerable attention in the fuzzy set community.  ...  Acknowledgements: The author is grateful to Thomas Sudkamp and Christophe Marsala for helpful comments and useful suggestions.  ... 
doi:10.1016/j.fss.2005.05.036 fatcat:oqtnulnpn5gitirvf5zhvn3k7e

Evolutionary Induction of Descriptive Rules in a Market Problem [chapter]

M.J. del Jesus, P. González, F. Herrera, M. Mesonero
2005 Studies in Computational Intelligence  
We study the use of Soft Computing methodologies, specifically Fuzzy Logic and Genetic Algorithms, in the design of the Data Mining algorithms most proper to this problem, descriptive induction algorithms  ...  Then we present an evolutionary model for the descriptive induction of fuzzy or crisp rules which describe subgroups.  ...  Acknowledgments This work was supported by the Spanish Ministry of Science and Technology and by the European Fund. FEDER under Projects TIC-04036-C05-01 and TIC-04036-C05-04.  ... 
doi:10.1007/11004011_14 fatcat:cnts5mwjwvdbbly7f52u4xboq4

Fuzzy sets in machine learning and data mining

Eyke Hüllermeier
2011 Applied Soft Computing  
This paper briefly reviews some typical applications and highlights potential contributions that fuzzy set theory can make to machine learning, data mining, and related fields.  ...  Machine learning, data mining, and several related research areas are concerned with methods for the automated induction of models and the extraction of interesting patterns from empirical data.  ...  Learning Fuzzy Rule-Based Systems The most frequent application of FST in machine learning is the induction or the adaptation of rule-based models.  ... 
doi:10.1016/j.asoc.2008.01.004 fatcat:5nfpsiwn5bfs3k25t5eg5fc5pe

Induction of Fuzzy Rules by Means of Artificial Immune Systems in Bioinformatics [chapter]

Filippo Menolascina, Vitoantonio Bevilacqua, Mariadele Zarrilli, Giuseppe Mastronardi
2009 Studies in Fuzziness and Soft Computing  
Fuzzy Rule Induction (FRI) is one of the main areas of research in the field of computational intelligence.  ...  In this chapter we will focus on a specific application of type-1 (T1) and type-2(T2) fuzzy systems to data mining in bioinformatics in which FRI is carried out using a novel and promising computational  ...  The first AIS for rule induction in the classification task of data mining was proposed in [3] , and named IFRAIS (Induction of Fuzzy Rules with an Artificial Immune System).  ... 
doi:10.1007/978-3-540-89968-6_1 fatcat:l4py6wps2vhkboc7j45cfiqg4a

Mini track: 'data and process mining'

S. Piramuthu, H.M. Chung
2004 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the  
The minitrack covers the broad theory and application issues related to data mining, machine learning, knowledge acquisition, knowledge discovery, information retrieval, data base, and inductive decision-making  ...  textmining, association rules, and fuzzy decision trees.  ...  The minitrack covers the broad theory and application issues related to data mining, machine learning, knowledge acquisition, knowledge discovery, information retrieval, data base, and inductive decision-making  ... 
doi:10.1109/hicss.2004.1265197 dblp:conf/hicss/PiramuthuC04 fatcat:bychholugnhf5m7u6b27i4slfm

Fuzzy inductive learning for multimedia mining

Marcin Detyniecki, Christophe Marsala
2001 European Society for Fuzzy Logic and Technology  
In this paper, we propose to extract knowledge from the whole kind of multimedia data and to bring up a collaborative fuzzy data mining process where each kind of data helps to extract a global knowledge  ...  The growing of multimedia data has caused a corresponding growth in the need to analyze and to exploit it.  ...  Fuzzy inductive learning and data mining Data mining (DM) was first introduced at the beginning of the 1990s.  ... 
dblp:conf/eusflat/DetynieckiM01 fatcat:lqvyb3mwqbeljfkasiq4j4ralq

Building Intelligent Learning Database Systems

Xindong Wu
2000 The AI Magazine  
For some applications, ment rule induction from (or data mining in) such as CAD and CAM where the data schema- databases, (2) designing a specific engine to ta  ...  ration for data mining. How to integrate data- 2.  ... 
doi:10.1609/aimag.v21i3.1524 dblp:journals/aim/Wu00 fatcat:hebibcyhmvafrow4ivzrkmo2hu

Web usage mining for predicting final marks of students that use Moodle courses

Cristobal Romero, Pedro G. Espejo, Amelia Zafra, Jose Raul Romero, Sebastian Ventura
2010 Computer Applications in Engineering Education  
Several wellknown classification methods have been used, such as statistical methods, decision trees, rule and fuzzy rule induction methods, and neural networks.  ...  We have also developed a specific Moodle mining tool oriented for the use of not only experts in data mining but also of newcomers like instructors and courseware authors.  ...  Educational Data Mining (EDM) is an emerging interdisciplinary research area that deals with the application of Data Mining (DM) techniques to educational data [14] .  ... 
doi:10.1002/cae.20456 fatcat:h5qocq3o6nfg3jbw5zf3q6o6pi

Preface

S.K Pal, A Skowron
2003 Pattern Recognition Letters  
and in combination, with applications to different facets of pattern recognition, in particular to data mining tasks.  ...  , data classification analysis, rule generation, machine learning, data mining and knowledge discovery.  ... 
doi:10.1016/s0167-8655(02)00195-2 fatcat:lvns5acycvaapfxwwvobe2x7ju

FARM: Fuzzy Action Rule Mining

Zahra Entekhabi, Pirooz Shamsinejadbabki
2018 International Journal of Advanced Computer Science and Applications  
Action Mining is a sub-field of Data Mining that concerns about finding ready-to-apply action rules.  ...  The majority of the patterns discovered by traditional data mining methods require analysis and further work by domain experts to be applicable in target domain while Action Mining methods try to find  ...  Data mining is a procedure which uses data analysis tools to find patterns and relationships between data.  ... 
doi:10.14569/ijacsa.2018.090134 fatcat:cyvvkdyjdbfprm6pxzdx5mpcsy
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