東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Rule based systems for big data = a ...

Liu, Han.

FindBook

Google Book

Amazon

博客來

Rule based systems for big data = a machine learning approach /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Rule based systems for big data/ by Han Liu, Alexander Gegov, Mihaela Cocea.
其他題名:	a machine learning approach /
作者:	Liu, Han.
其他作者:	Gegov, Alexander.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	xiii, 121 p. :ill. (some col.), digital ;24 cm.
內容註:	Introduction -- Theoretical Preliminaries -- Generation of Classification Rules -- Simplification of Classification Rules -- Representation of Classification Rules -- Ensemble Learning Approaches -- Interpretability Analysis.
Contained By:	Springer eBooks
標題:	System design. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-23696-4
ISBN:	9783319236964$q(electronic bk.)

Rule based systems for big data = a machine learning approach /
Liu, Han.

Rule based systems for big dataa machine learning approach /[electronic resource] :by Han Liu, Alexander Gegov, Mihaela Cocea. - Cham :Springer International Publishing :2016. - xiii, 121 p. :ill. (some col.), digital ;24 cm. - Studies in big data,v.132197-6503 ;. - Studies in big data ;v.1..

Introduction -- Theoretical Preliminaries -- Generation of Classification Rules -- Simplification of Classification Rules -- Representation of Classification Rules -- Ensemble Learning Approaches -- Interpretability Analysis.

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

ISBN: 9783319236964$q(electronic bk.)

Standard No.: 10.1007/978-3-319-23696-4doiSubjects--Topical Terms:

518843
System design.

LC Class. No.: QA76.9.S88

Dewey Class. No.: 004.21

Rule based systems for big data = a machine learning approach /
LDR:02002nmm a2200325 a 4500 001 2029135
003 DE-He213
005 20160721145615.0
006 m d
007 cr nn 008maaau
008 160908s2016 gw s 0 eng d
020 $a 9783319236964$q(electronic bk.)
020 $a 9783319236957$q(paper)
024 7 $a 10.1007/978-3-319-23696-4 $2 doi
035 $a 978-3-319-23696-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.S88
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 004.21 $2 23
090 $a QA76.9.S88 $b L783 2016
100 1 $a Liu, Han. $3 2095320
245 1 0 $a Rule based systems for big data $h [electronic resource] : $b a machine learning approach / $c by Han Liu, Alexander Gegov, Mihaela Cocea.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xiii, 121 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6503 ; $v v.13
505 0 $a Introduction -- Theoretical Preliminaries -- Generation of Classification Rules -- Simplification of Classification Rules -- Representation of Classification Rules -- Ensemble Learning Approaches -- Interpretability Analysis.
520 $a The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.
650 0 $a System design. $3 518843
650 0 $a Rule-based programming. $3 692014
650 0 $a Machine learning. $3 533906
650 0 $a Big data. $3 2045508
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
700 1 $a Gegov, Alexander. $3 1244376
700 1 $a Cocea, Mihaela. $3 2179967
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in big data ; $v v.1. $3 2055170
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-23696-4
950 $a Engineering (Springer-11647)