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Action rules mining /

Agnieszka Dardzinska.

Book Cover
Main Author: Dardzinska, Agnieszka.
Published: Berlin ; Springer, ©2013.
Series: Studies in computational intelligence ; 468.
Topics: Data mining. | Ingénierie.
Genres: Electronic books.
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100 1 |aDardzinska, Agnieszka.
245 10|aAction rules mining /|cAgnieszka Dardzinska.
260 |aBerlin ;|aNew York :|bSpringer,|c©2013.
300 |a1 online resource.
336 |atext|btxt|2rdacontent
337 |acomputer|bc|2rdamedia
338 |aonline resource|bcr|2rdacarrier
347 |atext file|bPDF|2rda
490 1 |aStudies in computational intelligence,|x1860-949X ;|v468
504 |aIncludes bibliographical references.
505 00|t1.|tIntroduction --|g2.|tInformation Systems --|g2.1.|tTypes of Information Systems --|g2.2.|tTypes of Incomplete Information Systems --|g2.3.|tSimple Query Language --|g2.3.1.|tStandard Interpretation of Queries in Complete Information Systems --|g2.3.2.|tStandard Interpretation of Queries in Incomplete Information Systems --|g2.4.|tRules --|g2.5.|tDistributed Information Systems --|g2.6.|tDecision Systems --|g2.7.|tPartially Incomplete Information Systems --|g2.8.|tExtracting Classification Rules --|g2.8.1.|tAttribute Dependency and Coverings --|g2.8.2.|tSystem LERS --|g2.8.3.|tAlgorithm for Finding the Set of All Coverings (LEM1) --|g2.8.4.|tAlgorithm LEM2 --|g2.8.5.|tAlgorithm for Extracting Rules from Incomplete --|gDecision System (ERID) --|g2.9.|tChase Algorithms --|g2.9.1.|tTableaux Systems and Chase --|g2.9.2.|tHandling Incomplete Values Using CHASE1 Algorithm --|g2.9.3.|tHandling Incomplete Values Using CHASE2 Algorithm --|gX Contents --|g3.|tActionRules --|g3.1.|tMain Assumptions --|g3.2.|tAction Rules from Classification Rules --|g3.2.1.|tSystem DEAR --|g3.2.2.|tSystem DEAR2 --|g3.3.|tE-action Rules --|g3.3.1.|tARAS Algorithm. --|g3.4.|tAction Rules Tightly Coupled Framework --|g3.5.|tCost and Feasibility. --|g3.6.|tAssociation Action Rules --|g3.6.1.|tFrequent Action Sets --|g3.7.|tRepresentative Association Action Rules --|g3.8.|tSimple Association Action Rules --|g3.9.|tAction Reducts --|g3.9.1.|tExperiments and Testing --|g3.10.|tMeta-action --|g3.10.1.|tDiscovering Action Paths.
520 |aWe are surrounded by data, numerical, categorical and otherwise, which must to be analyzed and processed to convert it into information that instructs, answers or aids understanding and decision making. Data analysts in many disciplines such as business, education or medicine, are frequently asked to analyze new data sets which are often composed of numerous tables possessing different properties. They try to find completely new correlations between attributes and show new possibilities for users. Action rules mining discusses some of data mining and knowledge discovery principles and then describe representative concepts, methods and algorithms connected with action. The author introduces the formal definition of action rule, notion of a simple association action rule and a representative action rule, the cost of association action rule, and gives a strategy how to construct simple association action rules of a lowest cost. A new approach for generating action rules from datasets with numerical attributes by incorporating a tree classifier and a pruning step based on meta-actions is also presented. In this book we can find fundamental concepts necessary for designing, using and implementing action rules as well. Detailed algorithms are provided with necessary explanation and illustrative examples.
546 |aEnglish.
650 0|aData mining.
650 7|aIngénierie.|2eclas
650 7|aData mining.|2fast|0(OCoLC)fst00887946
655 4|aElectronic books.
776 08|iPrinted edition|z9783642356490
830 0|aStudies in computational intelligence ;|v468.
852 8 |beresour-nc|hOnline Resource|t1|zAccessible anywhere on campus or with UIUC NetID
856 40|3SpringerLink - Full text online|u
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938 |aebrary|bEBRY|nebr10656814
938 |aYBP Library Services|bYANK|n9991619
994 |aC0|bUIU

Staff View for: Action rules mining