소장자료
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001 | 0093627329▲ | ||
005 | 20180519090746▲ | ||
008 | 160527s2016 nju 001 0 eng c▲ | ||
010 | ▼a2015040496▲ | ||
020 | ▼a9781118729274 (cloth)▲ | ||
040 | ▼aWaSeSS/DLC▼beng▼cWaSeSS▼d221016▲ | ||
042 | ▼apcc▲ | ||
050 | 0 | 0 | ▼aHF5548.2▼b.S44843 2016▲ |
082 | 0 | 0 | ▼a006.312▼223▲ |
090 | ▼a006.312▼bS558d3▲ | ||
100 | 1 | ▼aShmueli, Galit,▼d1971-▲ | |
240 | 1 | 0 | ▼aData mining for business intelligence▲ |
245 | 1 | 0 | ▼aData mining for business analytics :▼bconcepts, techniques, and applications in Microsoft Office Excel with XLMiner /▼cGalit Shmueli, Nitin R. Patel, Peter C. Bruce.▲ |
250 | ▼a3rd ed.▲ | ||
260 | ▼aHoboken, New Jersey :▼bJohn Wiley & Sons,▼c2016.▲ | ||
300 | ▼axxxi, 514 p. ;▼c26 cm.▲ | ||
500 | ▼aIncludes index.▲ | ||
500 | ▼aOriginally published as: Data mining for business intelligence, 2007.▲ | ||
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.▲ | |
630 | 0 | 0 | ▼aMicrosoft Excel (Computer file)▲ |
650 | 0 | ▼aBusiness▼xData processing.▲ | |
650 | 0 | ▼aData mining.▲ | |
700 | 1 | ▼aPatel, Nitin R.▼q(Nitin Ratilal)▲ | |
700 | 1 | ▼aBruce, Peter C.,▼d1953-▲ | |
999 | ▼a김진영▼c김정이▲ |
Data mining for business analytics :concepts, techniques, and applications in Microsoft Office Excel with XLMiner
자료유형
국외단행본
서명/책임사항
Data mining for business analytics : concepts, techniques, and applications in Microsoft Office Excel with XLMiner / Galit Shmueli, Nitin R. Patel, Peter C. Bruce.
통일표제
Data mining for business intelligence
개인저자
판사항
3rd ed.
발행사항
Hoboken, New Jersey : John Wiley & Sons , 2016.
형태사항
xxxi, 514 p. ; 26 cm.
일반주기
Includes index.
Originally published as: Data mining for business intelligence, 2007.
Originally published as: Data mining for business intelligence, 2007.
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.
ISBN
9781118729274 (cloth)
청구기호
006.312 S558d3
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