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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  
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.  ...  Case-based reasoning (CBR) is the process of solving new cases by retrieving the most relevant ones from an existing knowledge-base.  ...  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

Information Granulation and Pattern Recognition [chapter]

Andrzej Skowron, Roman W. Swiniarski
2004 Rough-Neural Computing  
In the overview of methods for feature selection, we discuss feature selection criteria based on the rough set approach and the relationships between them and other existing criteria.  ...  Our algorithm for feature selection used in the application reported is based on an application of the rough set method to the result of principal component analysis used for feature projection and reduction  ...  Feature Selection Based on Rough Sets The rough set approach to feature selection can be based on the minimal description length principle [40] and methods for tuning parameters of approximation spaces  ... 
doi:10.1007/978-3-642-18859-6_25 fatcat:jozyz7pezrdppeh2kmg7t3j6cy

Fuzzy-rough classifier ensemble selection

Ren Diao, Qiang Shen
2011 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011)  
In this paper, a new approach to classifier ensemble selection based on fuzzyrough feature selection and harmony search is proposed.  ...  Harmony search is then used to select a minimal subset of such artificial features that maximises the fuzzy-rough dependency measure.  ...  A data reduction approach for fuzzyrough feature selection (FRFS), based on fuzzy-rough sets [7] , has been developed [14] .  ... 
doi:10.1109/fuzzy.2011.6007400 dblp:conf/fuzzIEEE/DiaoS11 fatcat:awmvemny2na6bcwskptwk5lsua

Combining feature reduction and case selection in building CBR classifiers

Yan Li, S.C.K. Shiu, S.K. Pal
2006 IEEE Transactions on Knowledge and Data Engineering  
This paper presents a novel and fast approach to building efficient and competent CBR classifiers that combines both feature reduction (FR) and case selection (CS).  ...  It has three central contributions: 1) it develops a fast rough-set method based on relative attribute dependency among features to compute the approximate reduct, 2) it constructs and compares different  ...  FAST ROUGH SET-BASED FEATURE REDUCTION APPROACH The purpose of FR is to identify the most significant attributes and eliminate the irrelevant ones to form a good feature subset for classification tasks  ... 
doi:10.1109/tkde.2006.40 fatcat:3anvv25dwfgrlep3i7zncbsnnu

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).  ...  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

Soft computing techniques for web services brokering

Roy Ladner, Frederick Petry, Kalyan Moy Gupta, Elizabeth Warner, Philip Moore, David W. Aha
2008 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
IWB uses a case-based classifier to automatically discover Web Services. In this paper, we explore the use of rough set techniques for selecting features prior to classification.  ...  We demonstrate the effectiveness of this feature technique by comparing it with a leading non-rough set (Information Gain) feature selection technique.  ...  ACKNOWLEGMENT The authors would like to thank the Naval Research Laboratory's Base Program, Program Element No. 0602435N for sponsoring this research.  ... 
doi:10.1007/s00500-008-0277-0 fatcat:cwb6kxc5izhgnhmkatrbkqh6uy

Analysing Rough Sets weighting methods for Case-Based Reasoning Systems

M. Salamo, E. Golobardes
2002 Inteligencia Artificial  
Experiments using different domains show that weighting methods based on Rough Sets maintain or even improve the classification accuracy of Case-Based Reasoning Systems, compared to non-weighting approaches  ...  Case-Based Reasoning systems retrieve cases using a similarity function based on the K-NN or some derivatives. These functions are sensitive to irrelevant, interacting or noisy features.  ...  We would thank Enginyeria i Arquitectura La Salle (Ramon Llull University) for their support to our Research Group in Intelligent Systems.  ... 
doi:10.4114/ia.v6i15.753 fatcat:l7ng4oxw4nbc7lz54pfz3yowka

Rough Set Approach in Machine Learning: A Review

Prerna Mahajan, Rekha Kandwal, Ritu Vijay
2012 International Journal of Computer 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  ...  This paper discusses the basic concepts of rough set theory and point out some rough set-based research directions and applications.  ...  ] and others based on heuristic methods [13, 29, 30, 31] .Another evolutionary approach for feature selection based on RST proposed by Caballero et al  ... 
doi:10.5120/8924-2996 fatcat:skb3li5syvbe5kgsz63l43xp7a

Heuristic-based feature selection for rough set approach

U. Stańczyk, B. Zielosko
2020 International Journal of Approximate Reasoning  
Zielosko, Heuristic-based feature selection for rough set approach, Int.  ...  Discovered knowledge, represented in the form of generated decision rules, was employed to support feature selection and reduction process for induction of decision rules with classical rough set approach  ...  Rough set methods dedicated to feature selection are mainly based on al-110 gorithms for construction of reducts, and their different modifications.  ... 
doi:10.1016/j.ijar.2020.07.005 fatcat:mlcovuoylbdedlxt6ldhx42hhu

Classification of Complex Urban Fringe Land Cover Using Evidential Reasoning Based on Fuzzy Rough Set: A Case Study of Wuhan City

Yetao Yang, Yi Wang, Ke Wu, Xin Yu
2016 Remote Sensing  
To improve the recognition and handle the uncertainty, this paper provides a novel integrated approach, based on a fuzzy rough set and evidential reasoning (FRSER), for land cover classification in an  ...  A rough set-based imagery classifier is a rule-induction system that comprises a set of features (attributes) and the related decision rules for classification.  ...  Evidential Reasoning Based on Fuzzy Rough Set According to Equation (6) , the fuzzy rough set was interpreted to a DS theory-based evidential reasoning system.  ... 
doi:10.3390/rs8040304 fatcat:6bkq7c3mw5defi4otkhh6igyum

An Optimization Rough Set Boundary Region based Random Forest Classifier

Prerna Diwakar, Anand More
2017 International Journal of Computer Applications  
In this approach, we select significant attributes based on rough set theory with boundary region as an input to random forest classifier for constructing the decision tree is more efficient and scalable  ...  We proposed a novel hybrid approach combination of Rough Set with Boundary Region and Random Forest algorithm called Rough Set Boundary Region based Random Forest Classifier (RSBRRF Classifier) which is  ...  In this approach, we select significant attributes based on rough set theory with boundary region as an input to random forest classifier for constructing the decision tree is more efficient and scalable  ... 
doi:10.5120/ijca2017914024 fatcat:d4bbdverwnf5jg6nhqhie4bf24

An Efficient Hybrid Multilevel Intrusion Detection System in Cloud Environment

Partha Ghosh, Chameli Debnath, Dipjyoti Metia, Dr. Ruma Dutta
2014 IOSR Journal of Computer Engineering  
We use Rough Set Theory and Information Gain to select relevant features.  ...  Before classification, feature selection has been used to select relevant features.  ...  The Rough Set approach to processing of incomplete data is based on the lower and the upper approximation.  ... 
doi:10.9790/0661-16471626 fatcat:ribh3cmflra35fcyv4hjxrblxa

Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature

Abbas Mardani, Mehrbakhsh Nilashi, Jurgita Antucheviciene, Madjid Tavana, Romualdas Bausys, Othman Ibrahim
2017 Complexity  
Accordingly, the systematic and meta-analysis approach, which is called "PRISMA," has been proposed and the selected articles were classified based on the author and year of publication, author nationalities  ...  Based on the results of this review, we found that there are many challenging issues related to the different application area of fuzzy-rough set theory which can motivate future research studies.  ...  reasoning Table 5 : 5 Distribution papers based on feature or attribute selection.  ... 
doi:10.1155/2017/1608147 fatcat:o6khgyofg5g55hwgdj2y6angii

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  ...  for Values of Membership Attribute in Possibility-Based Fuzzy Relational Models p. 159 Foundations of Data Mining Research on Integrating Ordbms and Rough Set Theory p. 169 Feature Subset Selection  ... 
doi:10.1007/978-3-540-25929-9_3 fatcat:saiacsrpovgphlh5zzhoq4tcrq

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.  ...  ACKNOWLEDGMENT The authors want to thank the support lent by the local government of Xunta the Galicia, as well as the data facilitated by the CCCMM (Oceanographic Environment Quality Control Centre, Vigo  ... 
doi:10.1109/tsmcc.2006.876058 fatcat:6szwaj54sben3ik4oo5my7ekwi
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