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Fuzzy Distance Based Attribute Reduction in Decision Tables
2017
Research and Development on Information and Communication Technology
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In recent years, fuzzy rough set based attribute reduction has attracted the interest of many researchers. ...
In this paper, we propose a fuzzy distance based attribute reduction method on the decision table with numerical attribute value domain. ...
ATTRIBUTE REDUCTION BASED ON FUZZY DISTANCE MEASURE In this section, we present an attribute reduction method of the decision table with numerical attribute value using the fuzzy distance measure. ...
doi:10.32913/mic-ict-research-vn.v2.n36.356
fatcat:csu3j26gurajlm6p4pn2odjqxy
About a Fuzzy Distance between Two Fuzzy Partitions and Application in Attribute Reduction Problem
2016
Cybernetics and Information Technologies
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In recent years, researches have proposed methods based on fuzzy rough set approach to solve the problem of attribute reduction in decision tables with numerical value domain. ...
In this paper, we proposeafuzzy distance between two partitions and an attribute reduction method in numerical decision tables based on proposed fuzzy distance. ...
In this paper, we propose an attribute reduction method on the decision table with numerical attribute value which uses fuzzy distance based on fuzzy rough set. ...
doi:10.1515/cait-2016-0064
fatcat:hgor4kgpybektmdsmk253nj4ce
Hybrid Attribute Reduction for Classification Based on A Fuzzy Rough Set Technique
[chapter]
2005
Proceedings of the 2005 SIAM International Conference on Data Mining
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Based on the information measure, a general definition of significance of nominal, numeric and fuzzy attributes is presented. ...
In this paper a unified information measure is proposed to computing discernibility power of a crisp equivalence relation and a fuzzy one, which is the key concept in classical rough set model and fuzzy ...
A fuzzy-rough attribute reduction, called fuzzy-rough QUICKREDUCT algorithm, was given in [42] based on fuzzy dependency function. ...
doi:10.1137/1.9781611972757.18
dblp:conf/sdm/Hu05
fatcat:ekepggpu2vcyfgip7mzn47lknu
Distance Measure Assisted Rough Set Feature Selection
2007
IEEE International Fuzzy Systems conference proceedings
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The use of this measure in rough set feature selection can result in smaller subset sizes than those obtained using the dependency function alone. ...
This paper presents a novel rough set FS technique which uses the information of both the lower approximation dependency value and a distance metric for the consideration of objects in the boundary region ...
DISTANCE MEASURE ASSISTED ROUGH SET ATTRIBUTE REDUCTION As discussed previously, almost all techniques for rough set attribute reduction adopt an approach to minimisation that employs the information contained ...
doi:10.1109/fuzzy.2007.4295518
dblp:conf/fuzzIEEE/MacParthalainSJ07
fatcat:h2zkgp4pofbmra2dpyc4arz3i4
Modified Uncertainty Measure of Rough Fuzzy Sets from the Perspective of Fuzzy Distance
2018
Mathematical Problems in Engineering
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Then, from the perspective of fuzzy distance, we introduce a modified uncertainty measure based on the fuzziness-based uncertainty measure and present that our method not only is strictly monotonic with ...
As an extension of Pawlak's rough sets, rough fuzzy sets are proposed to deal with fuzzy target concept. ...
From the perspective of fuzzy distance, we present a modified fuzziness-based uncertainty measure for the rough fuzzy sets. ...
doi:10.1155/2018/4160905
fatcat:46m5apb565gzboyyyyl4la2mai
A Distance Measure Approach to Exploring the Rough Set Boundary Region for Attribute Reduction
2010
IEEE Transactions on Knowledge and Data Engineering
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The use of this measure in rough set feature selection can result in smaller subset sizes than those obtained using the dependency function alone. ...
Feature Selection (FS) or Attribute Reduction techniques are employed for dimensionality reduction and aim to select a subset of the original features of a data set which are rich in the most useful information ...
MEASURE ASSISTED ROUGH SET ATTRIBUTE REDUCTION As discussed previously, almost all techniques for rough set attribute reduction adopt an approach to minimization that examines only the information contained ...
doi:10.1109/tkde.2009.119
fatcat:vfdmnvirxzcfjjwx6caoupnnae
Information-preserving hybrid data reduction based on fuzzy-rough techniques
2006
Pattern Recognition Letters
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Based on the information measure, a general definition of significance of nominal, numeric and fuzzy attributes is presented. ...
In this paper, an information measure is proposed to computing discernibility power of a crisp equivalence relation or a fuzzy one, which is the key concept in classical rough set model and fuzzy-rough ...
A fuzzy-rough attribute reduction, called fuzzy-rough QUICKREDUCT algorithm, was given in Shen and Jensen, 2004 ) based on fuzzy dependency function. ...
doi:10.1016/j.patrec.2005.09.004
fatcat:krhmbjf6crfpbdzjf4cvu4pjky
Relative Knowledge Distance Measure of Intuitionistic Fuzzy Concept
2022
Electronics
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Knowledge distance is used to measure the difference between granular spaces, which is an uncertainty measure with strong distinguishing ability in a rough set. ...
Firstly, a micro-knowledge distance (md) based on information entropy is proposed to measure the difference between intuitionistic fuzzy information granules. ...
Zheng [36] proposed an improved roughness method to measure the uncertainty of covering-based rough intuitionistic fuzzy sets. ...
doi:10.3390/electronics11203373
fatcat:4pt2rfjnijfyfgoeij4ttedcoi
A Bit-Chain Based Algorithm for Problem of Attribute Reduction
[chapter]
2012
Lecture Notes in Computer Science
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One of key problems of knowledge acquisition in theoretical study of rough sets is attribute reduction. ...
Set of maximal random prior forms is put forward as an effective way for attribute reduction. ...
A Greedy Reduction Algorithm based on Consistency [18] and Distance Measure Assisted Rough Set Attribute Reduction
< a 1 a 2 2 … a m > ∩ < b 1 b 2 … b m > = < c 1 c 2 … c m >, a i , b i ∈ {0,1}, c i ...
doi:10.1007/978-3-642-28487-8_44
fatcat:ydns5mo65nfqxcabv4b6bmu5jq
Fuzzy distance-based filter-wrapper incremental algorithms for attribute reduction when adding or deleting attribute set
2021
Vietnam Journal of Science and Technology
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In this paper, we propose incremental algorithms that find reducts following filter-wrapper approach using fuzzy distance measure in the case of adding and deleting attribute set. ...
The fuzzy rough set theory is considered an effective tool to solve the attribute reduction problem directly on the original decision system, without data preprocessing. ...
using fuzzy distance when deleting attribute set is as follows: Algorithm IFW_FDAR_DA (Incremental Filter-Wrapper Fuzzy Distance-based Attribute Reduction Algorithm when Deleting Attributes). ...
doi:10.15625/2525-2518/59/2/15698
fatcat:k5ha24v7nnapvfp7qojpiszkf4
Fuzzy Rough Sets Theory Reducts for Quantitative Decisions – Approach for Spatial Data Generalization
[chapter]
2015
Lecture Notes in Computer Science
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The proposed method is based on the tnorm of fuzzy indiscernibility based on attribute value and fuzzy indiscernibility based on decision, which is calculated for each pair of objects. ...
Such tools as reducts and fuzzy reducts, though useful, are still insufficient for the quantitative decisions, common in cartographical generalization. ...
Fuzzy Rough Sets The hybrid of the fuzzy sets theory and rough sets theory, enabling to create fuzzy reducts, employs the attributes in quantitative scale. ...
doi:10.1007/978-3-319-19941-2_30
fatcat:tclxcqqohjbxlgupu6exbwes6i
Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation
2007
Pattern Recognition
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We derive several attribute significance measures based on the proposed fuzzy-rough model and construct a forward greedy algorithm for hybrid attribute reduction. ...
In this paper, we introduce a simple and efficient hybrid attribute reduction algorithm based on a generalized fuzzy-rough model. ...
In essence, all the measures can be divided into two classes: the distance-based measures and consistency-based measures. ...
doi:10.1016/j.patcog.2007.03.017
fatcat:e7d2bqld7vdj7ph7tozvblnlkq
Distance: A more comprehensible perspective for measures in rough set theory
2012
Knowledge-Based Systems
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Moreover, a rough set framework based on the set distance is also a very interesting perspective for understanding rough set approximation. ...
In this study, through introducing set distance and partition distance to rough set theory, we investigate how to understand measures from rough set theory in the viewpoint of distance, which are inclusion ...
Set distance and fuzziness measure of a rough set In this subsection, we will research the set distance characterization of the fuzziness measures of a rough set and a rough decision. Proposition 6. ...
doi:10.1016/j.knosys.2011.11.003
fatcat:u6k4rwjtrbfzfjmvzd6hdaoilm
Data Mining Based on Fuzzy Rough Set Theory and Its Application in the Glass Identification
2009
Modern Applied Science
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To overcome the disadvantage of determining artificially the class number, fuzzy C means clustering is introduced to fuzzify the continual attribute, and the best minute class number is obtained by cluster ...
The relationship of glass composition and its application is excavated using data mining method in this paper. ...
Eliminate redundant attributes used attribute reduction algorithm based on fuzzy rough set and structure new decision table, and then eliminate redundant attribute value of the new decision table. ...
doi:10.5539/mas.v3n8p100
fatcat:kbnjq63rebcbdmwj4r3koqgoje
Fuzzy - Rough Feature Selection With Π- Membership Function For Mammogram Classification
[article]
2012
arXiv
pre-print
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2012 pre-print arXiv:1205.4336v1 fatcat:wneffn4at5fzjlyfw6u4kusyma
In this paper, Fuzzy-Rough feature selection with π membership function is proposed. The selected features are used to classify the abnormalities with help of Ant-Miner and Weka tools. ...
If all the extracted features are used, most of the cases are misidentified. Hence feature selection procedure is sought. ...
(%)
Fuzzy Rough Quick
Reduct (%)
Fuzzy Rough Entropy
Based Quick Reduct (%)
Fuzzy Rough Quick
Reduct with π-
membership ...
arXiv:1205.4336v2
fatcat:hxkda5ha7zeuloh3lg7sdxpfda
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