Fuzzy-rough set
A Distributed Clustering Approach for Heterogeneous Environments Using Fuzzy Rough Set Theory
... propose a new instance weighting method based on fuzzy and rough set theory. To the best of our knowledge, most of instance weighting algorithms used distance between instances as a criterion for ...
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A Variable Precision Fuzzy Rough Set Approach to a Fuzzy Rough Decision Table
... precision rough set and fuzzy set. For fuzzy rough decision table, we convert fuzzy equivalence relation into equivalence relation through λ-cut set, and we ...
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The Application of Fuzzy-Rough Set Decision Tree for Credit Rating
... on fuzzy rough set for credit rating prediction in a micro credit bank in ...decision, fuzzy decision tree modeling, generate rules, and make prediction of new data with decision rules ...
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Diagnosis of Cancer using Fuzzy Rough Set Theory
... A medical decision making system based on SVM [1] combined with feature selection has been applied for diagnosing breast cancer.To diagnose breast cancer researchers commonly use machine learning methods andexperiments ...
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Comparison of Robust Nearest Neighbour fuzzy Rough Classifier (RNN-FRC) with KNN and NEC Classifiers
... — Fuzzy rough set, generalized from Pawlak’s rough sets, were introduced for dealing with continuous or fuzzy ...of fuzzy rough sets is sensitive to noisy samples, ...
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Breast Tissue Classification via Interval Type 2 Fuzzy Logic Based Rough Set
... Besides, rough set theory also can evaluate the data ...rules, rough set will identify pattern and relationship of the data to yield a sound ...word, Fuzzy rough set can ...
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An Exponential Kernel based Fuzzy Rough Sets Model for Feature Selection
... features. Fuzzy rough set plays a prominent role in dealing with imprecision and ...of fuzzy rough sets with kernel ...the fuzzy rough sets approach and an Exponential ...
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On bipolar fuzzy rough continuous functions
... bipolar fuzzy sets was introduced by Zhang [13] and Muthuraj ...of fuzzy rough continuous ...Bipolar fuzzy rough set and bipolar fuzzy rough topology ...
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A note on inequalities and critical values of fuzzy rough variables
... the fuzzy set of a fuzzy event can be given, which can be seen as a fuzzy rough ...of fuzzy rough sets by constructing a pair of upper and lower approximation operators of ...
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Granular computing with multiple granular layers for brain big data processing
... The rough set theory developed by Pawlak in 1982 is an effective model to acquire knowledge in information sys- tem with upper approximation and lower approximation as its core concepts, making decisions ...
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Multigranulation Decision theoretic Rough Set Based on Incomplete Interval valued Information Systems
... Pawlak rough set theory[1] is a powerful mathematical tool for uncertainty management, especially in describing the uncertainty of the ...data. Rough set theory has been widely used in many ...
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Attribute Reduction With Imputation Of Missing Data Using Fuzzy Rougsh Set
... data. Fuzzy rough attribute reduction with imputation (FRARI) algorithm has been proposed for attribute reduction with missing value imputation using fuzzy rough set based ...
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Empirical analysis of rough set categorical clustering techniques based on rough purity and value set
... In rough categorical clustering, mainly the data set is expressed as the decision table by introducing a decision ...data set aiming to find a cluster which best represents the data according to some ...
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A New Approach to Rough Lattices and Rough Fuzzy Lattices Based on Fuzzy Ideals
... Pawlak’s rough sets which was introduced by Pawlak [10] in the early 1980s, is an extension of classical set theory and could be regarded as a mathematical tool for several assessment and decision problems ...
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On Some Structural Properties of Fuzzy Soft Topological Spaces
... to set the membership function in each particular ...intuitionistic fuzzy sets is more generalized concept than the theory of fuzzy sets, but this theory has the same ...soft set via a ...
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Vol 1, No 1 (2013)
... Systems. Rough-set theory enhances databases by allowing it for the management of ...introduce rough relational databases. Rough Relational Databases (RRDB) are those databases that can have ...
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Association Rule Granulation using Rough Sets on Intuitionistic Fuzzy Approximation Spaces and Granular Computing
... In this section, to demonstrate our model we take into consideration an information system of a group of companies where we study the business strategies of different cosmetic companies in a country. In the Table 2 given ...
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Retrieving the Missing Information from Information Systems Using Rough Set, Covering Based Rough Set and Soft Set
... between rough set and covering based ...of rough set, attribute values are known but there are not enough attributes (or attribute domains are too coarse) to identify a single object by their ...
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Exploration Of Technique Involved In Image Retrieval Through Local Binary Pattern
... used fuzzy clustering methods is the fuzzy C-means (FCM) algorithm ...called fuzzy minimum has been redefined to enhance the classification of large data ...parallel fuzzy minimum (PFM) has ...
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FUZZY w- CONTINUOUS MAPPINGS
... Every fuzzy open (resp. fuzzy g-open) set is fuzzy w-open ...the fuzzy set B defined by B(a) = 0.5, B(b) = 0.5 in the fuzzy topological space (X,) of example ...is ...
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