Index. C, system, 8 Cech distance, 549

Similar documents
Andrzej Skowron, Zbigniew Suraj (Eds.) To the Memory of Professor Zdzisław Pawlak

Banacha Warszawa Poland s:

Rough Sets and Conflict Analysis

Classification Based on Logical Concept Analysis

A new Approach to Drawing Conclusions from Data A Rough Set Perspective

Drawing Conclusions from Data The Rough Set Way

A PRIMER ON ROUGH SETS:

ARPN Journal of Science and Technology All rights reserved.

Index. Cambridge University Press Relational Knowledge Discovery M E Müller. Index. More information

Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations

A Generalized Decision Logic in Interval-set-valued Information Tables

APPLICATION FOR LOGICAL EXPRESSION PROCESSING

Rough Set Model Selection for Practical Decision Making

Mathematical Approach to Vagueness

A Rough Set Interpretation of User s Web Behavior: A Comparison with Information Theoretic Measure

Handbook of Logic and Proof Techniques for Computer Science

Similarity-based Classification with Dominance-based Decision Rules

Research Article Special Approach to Near Set Theory

Interpreting Low and High Order Rules: A Granular Computing Approach

Characterizing Pawlak s Approximation Operators

ROUGH set methodology has been witnessed great success

An algorithm for induction of decision rules consistent with the dominance principle

Fuzzy Systems. Introduction

A Logical Formulation of the Granular Data Model

Propositional Logic: Models and Proofs

Approximate Boolean Reasoning: Foundations and Applications in Data Mining

Fuzzy Systems. Introduction

CS6375: Machine Learning Gautam Kunapuli. Decision Trees

Fuzzy and Rough Sets Part I

Uncertainty and Rules

REDUCTS AND ROUGH SET ANALYSIS

Introduction to Kleene Algebras

Data Analysis - the Rough Sets Perspective

Comparison of Rough-set and Interval-set Models for Uncertain Reasoning

On Rough Set Modelling for Data Mining

Foundations of Classification

ROUGH SETS THEORY AND DATA REDUCTION IN INFORMATION SYSTEMS AND DATA MINING

Clustering. CSL465/603 - Fall 2016 Narayanan C Krishnan

EEL 851: Biometrics. An Overview of Statistical Pattern Recognition EEL 851 1

Naive Bayesian Rough Sets

Applied Logic. Lecture 3 part 1 - Fuzzy logic. Marcin Szczuka. Institute of Informatics, The University of Warsaw

Computational Intelligence, Volume, Number, VAGUENES AND UNCERTAINTY: A ROUGH SET PERSPECTIVE. Zdzislaw Pawlak

Decision Tree Learning

Leveraging Data Relationships to Resolve Conflicts from Disparate Data Sources. Romila Pradhan, Walid G. Aref, Sunil Prabhakar

A Zadeh-Norm Fuzzy Description Logic for Handling Uncertainty: Reasoning Algorithms and the Reasoning System

Continuous Ordinal Clustering: A Mystery Story 1

Modern Information Retrieval

MATHEMATICS OF DATA FUSION

Semantics and Inference for Probabilistic Ontologies

1 Introduction Rough sets theory has been developed since Pawlak's seminal work [6] (see also [7]) as a tool enabling to classify objects which are on

UPPER AND LOWER SET FORMULAS: RESTRICTION AND MODIFICATION OF THE DEMPSTER-PAWLAK FORMALISM

Artificial Intelligence Programming Probability

A Crisp Representation for Fuzzy SHOIN with Fuzzy Nominals and General Concept Inclusions

On (Weighted) k-order Fuzzy Connectives

Multi-period medical diagnosis method using a single valued. neutrosophic similarity measure based on tangent function

Induction of Decision Trees

Role-depth Bounded Least Common Subsumers by Completion for EL- and Prob-EL-TBoxes

22c:145 Artificial Intelligence

Interval based Uncertain Reasoning using Fuzzy and Rough Sets

Discrete Math. Background Knowledge/Prior Skills Commutative and associative properties Solving systems of equations

Recurrent Neural Networks and Logic Programs

Approximate Boolean Reasoning Approach to Rough Sets and Data Mining

Feature Selection with Fuzzy Decision Reducts

Where are we? Operations on fuzzy sets (cont.) Fuzzy Logic. Motivation. Crisp and fuzzy sets. Examples

Sergey Shvydun NORMATIVE PROPERTIES OF MULTI-CRITERIA CHOICE PROCEDURES AND THEIR SUPERPOSITIONS: II

ENTROPIES OF FUZZY INDISCERNIBILITY RELATION AND ITS OPERATIONS

On the Structure of Rough Approximations

Encoding formulas with partially constrained weights in a possibilistic-like many-sorted propositional logic

Dominance-based Rough Set Approach Data Analysis Framework. User s guide

More Model Theory Notes

Classification of Voice Signals through Mining Unique Episodes in Temporal Information Systems: A Rough Set Approach

A Randomized Approach for Crowdsourcing in the Presence of Multiple Views

Granularity, Multi-valued Logic, Bayes Theorem and Rough Sets

Rough Sets, Rough Relations and Rough Functions. Zdzislaw Pawlak. Warsaw University of Technology. ul. Nowowiejska 15/19, Warsaw, Poland.

Research Article The Uncertainty Measure of Hierarchical Quotient Space Structure

Revised College and Career Readiness Standards for Mathematics

On the Relation of Probability, Fuzziness, Rough and Evidence Theory

Parameters to find the cause of Global Terrorism using Rough Set Theory

Hierarchical Structures on Multigranulation Spaces

Pei Wang( 王培 ) Temple University, Philadelphia, USA

Data Mining and Machine Learning

Elements of Representation Theory for Pawlak Information Systems

B best scales 51, 53 best MCDM method 199 best fuzzy MCDM method bound of maximum consistency 40 "Bridge Evaluation" problem

Information Retrieval Basic IR models. Luca Bondi

Bayes Theorem - the Rough Set Perspective

Roman Słowiński. Rough or/and Fuzzy Handling of Uncertainty?

Automata Theory and Formal Grammars: Lecture 1

Information Refinement and Revision for Medical Expert System Automated Extraction of Hierarchical Rules from Clinical Data

Reasoning with Uncertainty

2 WANG Jue, CUI Jia et al. Vol.16 no", the discernibility matrix is only a new kind of learning method. Otherwise, we have to provide the specificatio

CS626 Data Analysis and Simulation

The non-logical symbols determine a specific F OL language and consists of the following sets. Σ = {Σ n } n<ω

Semantic Rendering of Data Tables: Multivalued Information Systems Revisited

Notation Index. gcd(a, b) (greatest common divisor) NT-16

Granular Computing: Granular Classifiers and Missing Values

Outline. Logical Agents. Logical Reasoning. Knowledge Representation. Logical reasoning Propositional Logic Wumpus World Inference

Bulletin of the Transilvania University of Braşov Vol 10(59), No Series III: Mathematics, Informatics, Physics, 67-82

Statistical Model for Rough Set Approach to Multicriteria Classification

Propositional and Predicate Logic - II

Abstract model theory for extensions of modal logic

Transcription:

Index PF(A), 391 α-lower approximation, 340 α-lower bound, 339 α-reduct, 109 α-upper approximation, 340 α-upper bound, 339 δ-neighborhood consistent, 291 ε-approach nearness, 558 C, 443-2 system, 8 Cech distance, 549 abstract DIS-algebra, 389 IS-algebra, 394 NIS-algebra, 398 accuracy of approximation, 83 acyclic refinement, 347 affinity separation technique, 417 algorithm, 237 240 approach distance, 546 approach space, 549 approximation concept, 85 lower, 336 set, 80 upper, 336 approximation space, 90, 439, 442, 443, 459 generalized, 91 approximations, 229 232, 239, 241 association rule irreducible, 127 attribute, 80 condition, 83 in i.s.r. systems, 180 reduction, 183, 230, 294 selection, 110 significance, 111 Bayesian confirmation measure, 192 bisimulation, 531 bisimulation-based approximation, 540 Boolean reasoning, 87, 107 approximate, 131 boundary of X, 440 region, 80, 445 characteristic relation, 231 characterization, 608 class, 570 classification, 186, 202, 277 clustering function, 117 common attributes, 587, 591 complete, 559 composite property, 344 concept approximation, 85 exact in mereological model, 571 vague, 78 condition atttribute, 83 conflict, 138 conjunction function, 313 consecutive 1s property, 181 consistency assumption, 278 context inducing, 145

646 Index core, 86, 190 covering, 454, 459 covering-based rough sets, 438, 440 442, 459 criterion, 186, 206 cut, 112 on attribute, 137 data mining, 617 attribute, 83 class, 84 generalized, 84 rule, 84, 190, 206, 213 coverage, 214 irredundant, 213 length, 214 minimal, 121 true, 84 truth degree, 84 rule reduction, 435 system, 83 consistent, 84 inconsistent, 84 table, 83, 213 degenerated, 213 separable subtable, 213 deoxyribonucleic acid, 411 dependency of attributes, 85 description of a point, 547 deterministic information system, 382 deterministic information system algebra, 387 differentiation, 606 digraph, 424 discernibility function, 106, 132 decision relative, 108 matrix, 106, 133 decision relative, 108 relation, 87 discretization, 88, 113 of large data sets, 136 distance, 548 DNA molecular technique, 413 rough-set computing, 418 dominance, 188, 206 -based rough set approach, 186 cone, 188 relation, 231 233 Dow Jones Industrial Average, 501 DRSA, 186 dynamic programming approach, 215 E-approximation lower, 573 upper, 573 Ehrenfeucht and Pawlak seminar, 176 Ehrenfeucht, Andrzej, 176 elementary property, 338 encoding process, 424 equivalence relation, 230, 335 error approximation, 110 evaluation function of an i.s.r., 180 exclusive rule, 612 extension of approximation space, 98 external relation, 586 feature selection, 294 filter prime, 391 focusing mechanism, 608 framework, 446, 452 gaze tracking system, 479 gel electrophoresis technique, 418 graded ill-known set, 313 granular computing, 142 interactive rough, 145 granular concept, 587 description language, 592 hierarchy, 590 GCH, 587 hierarchy construction, 594 granule, 143 information, 143 of knowledge, 188 greatest definable subset, 183 hard coding the environment, 250 heterogeneous Euclidean-overlap metric function (HEOM), 281 higher order rule, 600 hydrogen bond, 412 i.s.r. systems, 179 ICHD-II

Index 647 International Classification of Headache ver 2.0, 606 IHD International Headache Society, 606 ill-known set, 311 implicant, 87 approximate, 88 prime, 87 implication function, 313 residual, 575 inclusion function, 91 inclusion property kernel, 347 inclusive rule, 614 incomplete information system, 383 indicator function, 250 indiscernibility relation, 80, 183, 263, 439, 440, 459 information granulation, 143 storage and retrieval systems, 175 system, 80, 181, 383 ingredient, 570 internal relation, 586 invariants, 249 inverted file, 180 jmaf, 185, 193 kernel functions, 493 Kleene connectives, 448 450 knowledge approximation algebra, 385 knowledge discovery, 229 231, 246 least definable superset, 183 LERS data mining system, 267 level-wise attribute selection, 595 linear separability, 492 Lipski, Witold, 178 lower approximation, 80, 188, 189, 206, 312, 313, 336, 445 lower approximation of a set X, 442 lower distance, 549 mapping lower-semi-continuous, 580 upper-semi-continuous, 580 measure of similarity Jaccard-Needham, 375 median of a decision class, 137 medical diagnosis, 606 minimum description length, 183 principle, 83 MIR, 463, 464, 466 mixed approximation, 346 MLEM2 rule induction algorithm, 267 model mereological for rough sets, 571 rough mereological for rough sets, 574 MPEG 7, 464, 466 multi-classification, 494 1-v-1, 495 multiple criteria sorting, 186, 205 music genre classification, 476 music information retrieval MIR, 463 music recommendation, 465, 468 music social networking systems, 467 NEAR system, 551 nearness, 547 necessity measure, 321 negative region, 445 rule, 612 neighborhood, 281 entropy, 289 mutual information, 290 rough sets, 280 neighbourhood of points, 552 nitrogen-containing base, 411 non-deterministic information system, 383 non-deterministic information system algebra, 395 non-linear transformation, 492 NP-hard problem, 410, 435 ontology approximation, 103 ordinal classification with monotonicity constraints, 186, 205 overlap, 570 parameterized approximations, 264 part, 570 partial order, 335 Pawlak and physicians, 178 approximations, 263

648 Index machine, 3 Zdzisław Ignacy, 2 Pawlak s approximation quality, 253 rough sets, 440, 442, 459 perception based computing, 151 perceptional vector analysis, 250 Polish school of Artificial Intelligence, 2 positive region, 445 region of X, 440 rule, 611 possibility distribution, 313 measure, 321 precision, 265 preference, 186, 187, 205, 206 prime filter, 391 implicant, 87 probabilistic approximations, 264 rule, 611 probe function, 550 process mining, 149 property of the n-ary relation, 338 property-driven approximation space, 338 pseudo-random number generator, 5 quadtrees, 257 quality approximation space, 98 concept approximation, 98 decision rule, 85 of approximation, 189 recall, 265 recursive granulations, 594 reduct, 86, 106, 190 -α, 109 approximate, 110 decision relative, 107 minimal, 133 region boundary, 80, 264 negative, 264 positive, 85, 264 region-of-interest, 546 neighbourhood, 546 relation discernibility, 87 indiscernibility, 80 relational roughification, 523 RHINOS, 607, 618 rough approximation quality, 253 inclusion, 574 membership function, 88 mereology, 92 patterns, 500 real functions, 500 representation of ill-known set, 319 set, 82, 206 based classifiers, 94 based logics, 139 theory, 3, 229 sets, 175, 439, 440, 448, 460 support vector clustering, 507 machines, 492 rule boundary, 265 certain, 267 extraction, 298 induction, 614 positive, 265 possible, 265 sample selection, 291 saturated sequent, 452 454 scalability, 131 semantics of a granular concept, 592 set approximation, 80 crisp, 81 rough, 82 set-valued information system, 229 231 similarity relation, 91, 230 similarity-based roughification, 520 social choice functions, 364 subordination relation, 439, 441, 443, 445, 448, 459 C, 444 sufficiently near, 559 supervaluationism, 626 support vector machines, 492

Index 649 clustering, 507 regression, 500 symbolic value grouping, 88, 117 symmetric kernel, 351 syntax of a granular concept, 592 system information, 80 t norm Łukasiewicz, 575 Archimedean, 575 minimum, 575 product, 575 terminological roughification, 533 the first mathematical model of Crick and Watson s DNA encoding, 3 the Pawlak approach to conflict analysis, 3 three-valued Kleene connectives, 439 logic, 438, 440, 443, 445, 459 non-deterministic matrix, 440 threshold, 553 tolerance relation, 91, 230 transitive closure, 336 translations, 252 uncertainty function, 91 upper approximation, 80, 188, 189, 206, 312, 313, 336, 445 of a set X, 442 vague concept, 78 vagueness, 79, 624 higher order, 101 value set reduction, 112 variable consistency, 186, 193 visual neighbourhood, 553 perception, 249 voting procedure, 364 amendment, 364 approval, 365 Black, 365 Borda, 364 Coombs, 365 Copeland, 364 Dodgson, 364 Hare, 365 max-min, 364 Nanson, 365 plurality, 364 runoff, 365 voting procedures agreement between, 374 comparison criteria, 365 distance between, 374 wisdom technology (Wistech), 154