MARC Record from marc_columbia

LEADER: 05214cam a2200589Mi 4500
001 15124725
005 20220703233821.0
006 m o d
007 cr cn|||||||||
008 170620s2017 fluad ob 001 0 eng d
035 $a(OCoLC)ocn995765927
035 $a(NNC)15124725
040 $aCRCPR$beng$erda$epn$cCRCPR$dOCLCO$dOCLCQ$dYDX$dORZ$dUAB$dU3W$dEBLCP$dMERUC$dOCLCQ$dOTZ$dWYU$dOCLCQ$dTYFRS$dOCLCQ$dUKAHL$dOCLCF$dOCLCO$dOCLCQ$dK6U$dOCLCO
019 $a1039422500$a1066624448$a1097947570$a1098158344$a1148228553
020 $a9781315156316$q(e-book)
020 $a1315156318
020 $a9781498797610$q(e-book ;$qPDF)
020 $a149879761X
020 $a9781351632546
020 $a135163254X
020 $z9781498797603$q(978-1-4987-9760-3)
020 $z1498797601$q(978-1-4987-9760-3)
024 7 $a10.1201/9781315156316$2doi
035 $a(OCoLC)995765927$z(OCoLC)1039422500$z(OCoLC)1066624448$z(OCoLC)1097947570$z(OCoLC)1098158344$z(OCoLC)1148228553
050 4 $aHF5415.126$b.R38 2017
082 14 $a658.872$bR236
082 04 $a658.872$bR236
049 $aZCUA
100 1 $aRatner, Bruce,$eauthor.
245 10 $aStatistical and machine-learning data mining :$btechniques for better predictive modeling and analysis of big data /$cBruce Ratner.
250 $aThird edition.
264 1 $aBoca Raton :$bCRC Press,$c[2017]
264 4 $c©2017
300 $a1 online resource (1 PDF (xxxiii, 655 pages)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
500 $a"Revised edition of the author's Statistical and machine-learning data mining, c2003"--Title page verso.
504 $aIncluded bibliographical references and index.
505 0 $aPreface -- Preface to second edition -- Acknowledgments -- About the author -- Introduction -- Science dealing with data: statistic and data science -- Basic data mining methods for variable assessment -- CHAID-based data mining for paired-variable assessment -- The importance of straight data : simplicity and desirability for good model-building practice -- Symmetrizing ranked data : a statistical data mining method for improving the predictive power of data -- Principal component analysis : a statistical data mining -- Method for many-variable assessment -- Market share estimation : data mining for an exception case -- The correlation coefficient : its values range between plus and minus 1, or do they? -- Logistic regression : the workhorse of response modeling -- Predicting share of wallet without survey data -- Ordinary regression: the workhorse of profit modeling -- Variable selection methods in regression: ignorable problem, notable solution -- CHAID for interpreting a logistic regression model -- The importance of the regression coefficient -- The average correlation: a statistical data mining measure -- For assessment of competing predictive models and the importance of the predictor variables -- CHAID for specifying a model with interaction variables -- Market segmentation classification modeling with logistic regression -- Market segmentation based on time-series data using latent class analysis -- Market segmentation: an easy way to understand the segments -- CHAID as a method for filling in missing values -- Model building with big complete and incomplete data -- Art, science, numbers, and poetry -- Identifying your best customers: descriptive, predictive, and look-alike profiling -- Assessment of marketing models -- Decile analysis: perspective and performance -- Net T-C lift model : assessing the net effects of test and control campaigns -- Bootstrapping in marketing -- Validating the logistic regression model : try bootstrapping -- Visualization of marketing models data mining to uncover innards of a model -- The predictive contribution coefficient : a measure of predictive importance -- Regression modeling involves art, science, and poetry, too -- Genetic and statistic regression models : a comparison -- Data reuse : a powerful data mining effect of the GenIQ model -- A data mining method for moderating outliers instead -- Of discarding them -- Overfitting : old problem, new solution -- The importance of straight data : revisited -- The geniq model : its definition and an application -- Finding the best variables for marketing models -- Interpretation of coefficient-free models -- Text mining : primer, illustration, and txtdm software -- Some of my favorite statistical subroutines -- Index.
588 0 $aOnline resource; title from digital title page (viewed on June 20, 2018).
650 0 $aDatabase marketing$xStatistical methods.
650 0 $aData mining$xStatistical methods.
650 0 $aBig data$xStatistical methods.
650 6 $aBases de données$xMarketing$xMéthodes statistiques.
650 6 $aDonnées volumineuses$xMéthodes statistiques.
650 7 $aData mining$xStatistical methods.$2fast$0(OCoLC)fst02007323
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$z9781498797603
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15124725$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS