소장자료
| LDR | 01521cam a2200289 a 4500 | ||
| 001 | 0093802987▲ | ||
| 005 | 20180520135335▲ | ||
| 008 | 170608s2018 njua 001 0 eng c▲ | ||
| 010 | ▼a2017024503▲ | ||
| 020 | ▼a9781118879368 (cloth)▲ | ||
| 035 | ▼a(KERIS)REF000018442911▲ | ||
| 040 | ▼aWaSeSS/DLC▼beng▼cWaSeSS▼dDLC▼d221016▲ | ||
| 042 | ▼apcc▲ | ||
| 050 | 0 | 0 | ▼aHF5548.2▼b.S55 2017▲ |
| 082 | 0 | 0 | ▼a006.312▼a658.4/03802856312▼223▲ |
| 090 | ▼a006.312▼bD232sA▲ | ||
| 245 | 0 | 0 | ▼aData mining for business analytics :▼bconcepts, techniques, and applications in R /▼cby Galit Shmuel...[et al.]▲ |
| 260 | ▼aHoboken, New Jersey :▼bJohn Wiley & Sons,▼c2018.▲ | ||
| 300 | ▼axxix, 544 p. :▼bill. ;▼c26 cm.▲ | ||
| 500 | ▼aIncludes index.▲ | ||
| 505 | 0 | ▼aOverview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- k-Nearest Neighbors (kNN) -- The Naive Bayes classifier -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant analysis -- Combining methods : ensembles and uplift modeling -- Association rules and collaborative filtering -- Cluster analysis -- Handling time series -- Regression-based forecasting -- Smoothing methods -- Social network analytics -- Text mining -- Cases.▲ | |
| 650 | 0 | ▼aBusiness▼xData processing.▲ | |
| 650 | 0 | ▼aData mining.▲ | |
| 650 | 0 | ▼aR (Computer program language)▲ | |
| 650 | 0 | ▼aBusiness mathematics▼xComputer programs.▲ | |
| 700 | 1 | ▼aShmueli, Galit,▼d1971-▲ | |
| 999 | ▼a정재훈▼c김미선▲ |
Data mining for business analytics :concepts, techniques, and applications in R
자료유형
국외단행본
서명/책임사항
Data mining for business analytics : concepts, techniques, and applications in R / by Galit Shmuel...[et al.]
발행사항
Hoboken, New Jersey : John Wiley & Sons , 2018.
형태사항
xxix, 544 p. : ill. ; 26 cm.
일반주기
Includes index.
내용주기
Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- k-Nearest Neighbors (kNN) -- The Naive Bayes classifier -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant analysis -- Combining methods : ensembles and uplift modeling -- Association rules and collaborative filtering -- Cluster analysis -- Handling time series -- Regression-based forecasting -- Smoothing methods -- Social network analytics -- Text mining -- Cases.
주제
ISBN
9781118879368 (cloth)
청구기호
006.312 D232sA
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