Theoretical preliminaries

Han Liu; Alexander Gegov; Mihaela Cocea

doi:10.1007/978-3-319-23696-4_2

Theoretical preliminaries

Han Liu, Alexander Gegov, Mihaela Cocea

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Abstract

As mentioned in Chap. 1, some fundamental concepts strongly relate to rule based systems and machine learning, including discrete mathematics, statistics, if-then rules, algorithms, logic and statistical measures of rule quality.

Original language	English
Title of host publication	Rule Based Systems for Big Data
Subtitle of host publication	A Machine Learning Approach
Publisher	Springer
Pages	11-27
Number of pages	17
Edition	1st
ISBN (Electronic)	9783319236964
ISBN (Print)	9783319236957, 9783319370279
DOIs	https://doi.org/10.1007/978-3-319-23696-4_2 https://doi.org/10.1007/978-3-319-23696-4
Publication status	Published - 17 Sept 2015

Publication series

Name	Studies in Big Data
Volume	13
ISSN (Print)	2197-6503
ISSN (Electronic)	2197-6511

Keywords

ensemble learning
rule base system
rule representation
single rule
truth table

Access to Document

https://link.springer.com/book/10.1007/978-3-319-23696-4

Cite this

@inbook{c0cee1ad48744f998db3cb1465b4a798,

title = "Theoretical preliminaries",

abstract = "As mentioned in Chap. 1, some fundamental concepts strongly relate to rule based systems and machine learning, including discrete mathematics, statistics, if-then rules, algorithms, logic and statistical measures of rule quality.",

keywords = "ensemble learning, rule base system, rule representation, single rule, truth table",

author = "Han Liu and Alexander Gegov and Mihaela Cocea",

year = "2015",

month = sep,

day = "17",

doi = "10.1007/978-3-319-23696-4_2",

language = "English",

isbn = "9783319236957",

series = "Studies in Big Data",

publisher = "Springer",

pages = "11--27",

booktitle = "Rule Based Systems for Big Data",

edition = "1st",

}

TY - CHAP

T1 - Theoretical preliminaries

AU - Liu, Han

AU - Gegov, Alexander

AU - Cocea, Mihaela

PY - 2015/9/17

Y1 - 2015/9/17

N2 - As mentioned in Chap. 1, some fundamental concepts strongly relate to rule based systems and machine learning, including discrete mathematics, statistics, if-then rules, algorithms, logic and statistical measures of rule quality.

AB - As mentioned in Chap. 1, some fundamental concepts strongly relate to rule based systems and machine learning, including discrete mathematics, statistics, if-then rules, algorithms, logic and statistical measures of rule quality.

KW - ensemble learning

KW - rule base system

KW - rule representation

KW - single rule

KW - truth table

UR - http://www.scopus.com/inward/record.url?scp=85132880121&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-23696-4_2

DO - 10.1007/978-3-319-23696-4_2

M3 - Chapter (peer-reviewed)

AN - SCOPUS:85132880121

SN - 9783319236957

SN - 9783319370279

T3 - Studies in Big Data

SP - 11

EP - 27

BT - Rule Based Systems for Big Data

PB - Springer

ER -

Theoretical preliminaries

Abstract

Publication series

Keywords

Access to Document

Fingerprint

Cite this