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Applying Rough Sets Reduction Techniques to the Construction of a Fuzzy Rule Base for Case Based Reasoning [chapter]

Florentino Fdez-Riverola, Fernando Díaz, Juan M. Corchado
2004 Lecture Notes in Computer Science  
This paper proposes a reduction technique based on Rough Sets theory that is able to minimize the case base by analyzing the contribution of each feature.  ...  Early work on Case Based Reasoning reported in the literature shows the importance of soft computing techniques applied to different stages of the classical 4-step CBR life cycle.  ...  The paper is structured as follows: section 2 introduces the Rough Set theory grounding; section 3 details the proposed Rough Set reduction technique; section 4 describes the Case-Based Reasoning platform  ... 
doi:10.1007/978-3-540-30498-2_9 fatcat:ia25y4e5wbh6poukkzkptf5lp4

Deleting and Building Sort Out Techniques for Case Base Maintenance [chapter]

Maria Salamó, Elisabet Golobardes
2002 Lecture Notes in Computer Science  
All the sort out techniques proposed are based on the same principle: a Rough Sets competence model. First of all, we present sort out reduction techniques based on deletion of cases.  ...  Early work on case based reasoning reported in the literature shows the importance of case base maintenance for successful practical systems.  ...  Aha for providing the IBL code as well as D. Randall Wilson and Tony R. Martinez who provided the code of the other reduction techniques.  ... 
doi:10.1007/3-540-46119-1_27 fatcat:kkxtm6iasnfzhkunwcalvdh4oq

Reducing the Memory Size of a Fuzzy Case-Based Reasoning System Applying Rough Set Techniques

F. Fernndez-Riverola, F. Daz, J. M. Corchado
2007 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
This paper proposes a reduction technique based on Rough Sets Theory capable of minimizing the case memory by analyzing the contribution of each case feature.  ...  Early work on Case Based Reasoning reported in the literature shows the importance of soft computing techniques applied to different stages of the classical 4-step CBR life cycle.  ...  for CBR systems while section III describes the Case-Based Reasoning platform used in this study; section IV introduces the Rough Set theory grounding and section V details the proposed Rough Set reduction  ... 
doi:10.1109/tsmcc.2006.876058 fatcat:6szwaj54sben3ik4oo5my7ekwi

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

Masahiro Inuiguchi
2004 Lecture Notes in Computer Science  
ß-Reduct Selection in the Variable Precision Rough Sets Model p. 412 Spatial Reasoning A Logic-Based Framework for Qualitative Spatial Reasoning in Mobile GIS Environment p. 418 Spatial Object  ...  Rough Approximations under Level Fuzzy Sets p. 78 Fuzzy-Rough Modus Ponens and Modus Tollens as a Basis for Approximate Reasoning p. 84 Logic and Rough Sets Rough Truth, Consequence, Consistency  ... 
doi:10.1007/978-3-540-25929-9_3 fatcat:saiacsrpovgphlh5zzhoq4tcrq

A rough set-based case-based reasoner for text categorization

Y. Li, S.C.K. Shiu, S.K. Pal, J.N.K. Liu
2006 International Journal of Approximate Reasoning  
This paper presents a novel rough set-based case-based reasoner for use in text categorization (TC).  ...  Finally, this smaller set of documents with fewer feature terms is used in TC. The proposed rough set-based case-based reasoner was tested on the Reuters21578 text datasets.  ...  Rough set-based feature term reduction To tackle the task of feature term extraction in the case-based reasoner, this paper develops a rough set-based approach.  ... 
doi:10.1016/j.ijar.2005.06.019 fatcat:37if36qbhvak5mwcmw4wnwwkfe

A Fuzzy-Rough Approach for Case Base Maintenance [chapter]

Guoqing Cao, Simon Shiu, Xizhao Wang
2001 Lecture Notes in Computer Science  
This paper proposes a fuzzy-rough method of maintaining Case-Based Reasoning (CBR) systems.  ...  by the rough set technique.  ...  future reasoning for a particular set of performance objectives".  ... 
doi:10.1007/3-540-44593-5_9 fatcat:febftivwkfhmrnzab3xm7ohfie

Ontology granularity and rough equality of concepts

Pavel Klinov, Lawrence J. Mazlack
2009 2009 IEEE International Conference on Systems, Man and Cybernetics  
An important advance was the attempt to employ Fuzzy Sets and Fuzzy Logic techniques in representing ontologies for intrinsically vague domains of interest where most of human knowledge cannot be expressed  ...  This will be useful for estimating appropriateness of existing ontologies for reasoning in incomplete domains.  ...  To address these issues we use Rough Sets [3] and Rough-Fuzzy Sets [4] techniques.  ... 
doi:10.1109/icsmc.2009.5345921 dblp:conf/smc/MazlackK09 fatcat:zl6uonitl5g5xoq2jxjzijkvee

H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus

Rahman Ali, Jamil Hussain, Muhammad Siddiqi, Maqbool Hussain, Sungyoung Lee
2015 Sensors  
First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST) based techniques and algorithms are used to mine the prediction rules.  ...  To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM) that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM) and type-  ...  These are defined for activation of HRBR, rough set-based reasoning, reference range-based reasoning and final results propagation.  ... 
doi:10.3390/s150715921 pmid:26151207 pmcid:PMC4541861 fatcat:cffqfz4lijclldmduwwht7ywkm

A combined data mining approach using rough set theory and case-based reasoning in medical datasets

Mohammad Taghi Rezvan, Ali Zeinal Hamadani, Babak Saffari, Ali Shalbafzadeh
2014 Decision Science Letters  
Case-based reasoning (CBR) is the process of solving new cases by retrieving the most relevant ones from an existing knowledge-base.  ...  This paper uses rough set theory (RST) in order to reduce the number of dimensions in a CBR classifier with the aim of increasing accuracy and efficiency.  ...  Li et al. (2006) presented a novel rough set-based case-based reasoner for application of text categorization.  ... 
doi:10.5267/j.dsl.2014.4.003 fatcat:5zywkrrwpnhyfiaqnd7g6gy2p4

Page 7911 of Mathematical Reviews Vol. , Issue 99k [page]

1999 Mathematical Reviews  
Wong, A rough-set model for reasoning about knowledge (276-285); Y. Y. Yao, Generalized rough set models (286-318). Part 3. Jan G.  ...  on rough sets—the ROSETTA system (376-399); Wojciech Kowal- czyk, Rough data modelling: a new technique for analyzing data (400-421); Marzena Kryszkiewicz, Properties of incomplete infor- mation systems  ... 

Symptoms Reduction Using Rough Sets Based Traditional Chinese Medicine Stomachache Diagnosis

Ruixiang Wang, Yang Zhou, Hao Yuan, Xingliang Qi
2016 ICIC Express Letters  
Finally, 18 symptoms reduction sets to differentiate each TCM syndrome and 30 core symptoms of stomachache were achieved based on the rough sets theory and 279 TCM diagnostic cases.  ...  As an important concept in rough sets theory, attributes reduction can provide "the most valuable symptoms" for different stomachache syndromes in Traditional Chinese Medicine (TCM).  ...  We would like to express our sincere gratitude to the reviewers, for their instructive advice and useful suggestions on our thesis.  ... 
doi:10.24507/icicel.10.08.1895 fatcat:xsbvkowhxfabvfbo64cjwty4bi

Rough Set Approach in Machine Learning: A Review

Prerna Mahajan, Rekha Kandwal, Ritu Vijay
2012 International Journal of Computer Applications  
This paper discusses the basic concepts of rough set theory and point out some rough set-based research directions and applications.  ...  The discussion also includes a review of rough set theory in various machine learning techniques like clustering, feature selection and rule induction. General Terms  ...  [72] have proposed a rough set technique for selecting a cluster attribute.  ... 
doi:10.5120/8924-2996 fatcat:skb3li5syvbe5kgsz63l43xp7a

A Survey of Software Packages Used for Rough Set Analysis

Zain Abbas, Aqil Burney
2016 Journal of Computer and Communications  
Rough Set Theory (RST) is a technique used in soft computing that enhances the idea of classical sets to deal with incomplete knowledge and provides a mechanism for concept approximation.  ...  The paper provides a survey of packages that are most frequently used to perform data analysis based on Rough Sets.  ...  Rough Sets [20] It is a free package for R language that facilitates data analysis using techniques put forth by Rough Set and Fuzzy Rough Set Theories.  ... 
doi:10.4236/jcc.2016.49002 fatcat:nkly23aeefcjzihghkvturkr6m

A Comparative Study on Decision Rule Induction for incomplete data using Rough Set and Random Tree Approaches

M. Sandhya
2013 IOSR Journal of Computer Engineering  
The result of simple classification technique (using random tree classifier) is compared with the result of rough set attribute reduction performed based on Rule induction and decision tree.  ...  WEKA (Waikato Environment for Knowledge Analysis), a Data Mining tool and ROSE2 (Rough Set Data Explorer), a Rough Set approach tool have been used for the experiment.  ...  Experiment Results And Performance Evaluation In this experiment a comparative study of attribute reduction of rough set and classification technique of data mining technique for incomplete dataset on  ... 
doi:10.9790/0661-0930610 fatcat:emyh22ajefetzpof4xzr66ofvm

Hybrid Tolerance Rough Set

G. Jothi, H. Hannah Inbarani, Ahmad Taher Azar
2013 International Journal of Fuzzy System Applications  
In this paper, a novel supervised feature selection in mammogram images, using Tolerance Rough Set -PSO based Quick Reduct (STRSPSO-QR) and Tolerance Rough Set -PSO based Relative Reduct (STRSPSO-RR),  ...  This paper proposes an approach based on the tolerance rough set model, which has the flair to deal with real-valued data whilst simultaneously retaining dataset semantics.  ...  Rough set is a powerful tool for data reduction based on dependency between attributes.  ... 
doi:10.4018/ijfsa.2013100102 fatcat:tgd7n34ebfdmdgxxzwwksiqzoi
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