LEADER 03496nam 2200649Ia 450 001 9910146116903321 005 20230721005332.0 010 $a9786612007507 010 $a1-282-00750-5 010 $a1-4443-0307-4 010 $a1-4443-0308-2 035 $a(CKB)1000000000722799 035 $a(EBL)416545 035 $a(OCoLC)476248825 035 $a(SSID)ssj0000242182 035 $a(PQKBManifestationID)11191423 035 $a(PQKBTitleCode)TC0000242182 035 $a(PQKBWorkID)10299874 035 $a(PQKB)10510402 035 $a(MiAaPQ)EBC416545 035 $a(Au-PeEL)EBL416545 035 $a(CaPaEBR)ebr10300776 035 $a(CaONFJC)MIL200750 035 $a(OCoLC)438702676 035 $a(EXLCZ)991000000000722799 100 $a20080124d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 04$aThe science of compassionate love$b[electronic resource] $etheory, research, and applications /$fedited by Beverley Fehr, Susan Sprecher, and Lynn G. Underwood 210 $aMalden, MA $cWiley-Blackwell$d2009 215 $a1 online resource (488 p.) 300 $aDescription based upon print version of record. 311 $a1-4051-5394-6 311 $a1-4051-5393-8 320 $aIncludes bibliographical references and index. 327 $aThe Science of Compassionate Love; Contents; Contributors; Preface and Acknowledgments; Part I Definitions, Theory, and Measurement; 1 Compassionate Love: A Framework for Research; 2 Compassionate Love: Conceptual, Measurement, and Relational Issues; 3 Measuring Prosocial Behavior, Altruism, and Compassionate Love on US Television; Part II The Sociodemographics of Compassionate Love; 4 Loving and Caring in the United States: Trends and Correlates of Empathy, Altruism, and Related Constructs 327 $a5 Compassionate Motivation and Compassionate Acts across the Adult Life Course: Evidence from US National StudiesPart III Compassionate Love in Close Relationships; 6 Empathy and Compassionate Love in Early Childhood: Development and Family Influence; 7 Compassionate Love in Early Marriage; Part IV Compassionate Love for Non-Close Others; 8 A Behavioral Systems Perspective on Compassionate Love; 9 Compassionate Acts: Motivations for and Correlates of Volunteerism among Older Adults; 10 Compassionate Love for Ind 330 $aThe Science of Compassionate Love is an interdisciplinary volume that presents cutting-edge scholarship on the topics of altruism and compassionate love. The book.; Adopts a social science approach to understanding compassionate love.; Emphasizes positive features of social interaction.; Encourages the appropriate expression of compassionate love both to those in intimate relationships and to strangers.; Includes articles by distinguished contributors from the fields of Psychology, Sociology, Communication Studies, Family Studies, Epidemiology, Medicine and Nursing.; Is ideal for workshops on 606 $aCompassion 606 $aEmotions 615 0$aCompassion. 615 0$aEmotions. 676 $a152.41 676 $a177.7 701 $aFehr$b Beverley Anne$f1958-$0935983 701 $aGordon$b Lynn Underwood$0935984 701 $aSprecher$b Susan$f1955-$0933344 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910146116903321 996 $aThe science of compassionate love$92108451 997 $aUNINA LEADER 05331nam 2200661 450 001 9910812118003321 005 20200520144314.0 010 $a1-118-72769-X 010 $a1-118-72793-2 035 $a(CKB)2550000001256699 035 $a(EBL)1662190 035 $a(SSID)ssj0001211417 035 $a(PQKBManifestationID)11782320 035 $a(PQKBTitleCode)TC0001211417 035 $a(PQKBWorkID)11205278 035 $a(PQKB)10247432 035 $a(MiAaPQ)EBC1662190 035 $a(Au-PeEL)EBL1662190 035 $a(CaPaEBR)ebr10856845 035 $a(CaONFJC)MIL588422 035 $a(OCoLC)878149193 035 $a(PPN)186134347 035 $a(EXLCZ)992550000001256699 100 $a20140414h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aApplied predictive analytics $eprinciples and techniques for the professional data analyst /$fDean Abbott 210 1$aIndianapolis, Indiana :$cJohn Wiley & Sons,$d2014. 210 4$dİ2014 215 $a1 online resource (453 p.) 300 $aIncludes index. 311 $a1-118-72796-7 311 $a1-306-57171-5 327 $aCover; Title Page; Copyright; Contents; Chapter 1 Overview of Predictive Analytics; What Is Analytics?; What Is Predictive Analytics?; Supervised vs. Unsupervised Learning; Parametric vs. Non-Parametric Models; Business Intelligence; Predictive Analytics vs. Business Intelligence; Do Predictive Models Just State the Obvious?; Similarities between Business Intelligence and Predictive Analytics; Predictive Analytics vs. Statistics; Statistics and Analytics; Predictive Analytics and Statistics Contrasted; Predictive Analytics vs. Data Mining; Who Uses Predictive Analytics? 327 $aChallenges in Using Predictive AnalyticsObstacles in Management; Obstacles with Data; Obstacles with Modeling; Obstacles in Deployment; What Educational Background Is Needed to Become a Predictive Modeler?; Chapter 2 Setting Up the Problem; Predictive Analytics Processing Steps: CRISP-DM; Business Understanding; The Three-Legged Stool; Business Objectives; Defining Data for Predictive Modeling; Defining the Columns as Measures; Defining the Unit of Analysis; Which Unit of Analysis?; Defining the Target Variable; Temporal Considerations for Target Variable 327 $aDefining Measures of Success for Predictive ModelsSuccess Criteria for Classification; Success Criteria for Estimation; Other Customized Success Criteria; Doing Predictive Modeling Out of Order; Building Models First; Early Model Deployment; Case Study: Recovering Lapsed Donors; Overview; Business Objectives; Data for the Competition; The Target Variables; Modeling Objectives; Model Selection and Evaluation Criteria; Model Deployment; Case Study: Fraud Detection; Overview; Business Objectives; Data for the Project; The Target Variables; Modeling Objectives 327 $aModel Selection and Evaluation CriteriaModel Deployment; Summary; Chapter 3 Data Understanding; What the Data Looks Like; Single Variable Summaries; Mean; Standard Deviation; The Normal Distribution; Uniform Distribution; Applying Simple Statistics in Data Understanding; Skewness; Kurtosis; Rank-Ordered Statistics; Categorical Variable Assessment; Data Visualization in One Dimension; Histograms; Multiple Variable Summaries; Hidden Value in Variable Interactions: Simpson's Paradox; The Combinatorial Explosion of Interactions; Correlations; Spurious Correlations; Back to Correlations; Crosstabs 327 $aData Visualization, Two or Higher DimensionsScatterplots; Anscombe's Quartet; Scatterplot Matrices; Overlaying the Target Variable in Summary; Scatterplots in More Than Two Dimensions; The Value of Statistical Significance; Pulling It All Together into a Data Audit; Summary; Chapter 4 Data Preparation; Variable Cleaning; Incorrect Values; Consistency in Data Formats; Outliers; Multidimensional Outliers; Missing Values; Fixing Missing Data; Feature Creation; Simple Variable Transformations; Fixing Skew; Binning Continuous Variables; Numeric Variable Scaling; Nominal Variable Transformation 327 $aOrdinal Variable Transformations 330 $a Learn the art and science of predictive analytics - techniques that get results Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory behind predictive analytics, teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks that are essential for successful p 606 $aBusiness$xData processing 606 $aBusiness planning$xData processing 606 $aBusiness$xComputer programs 615 0$aBusiness$xData processing. 615 0$aBusiness planning$xData processing. 615 0$aBusiness$xComputer programs. 676 $a006.312 700 $aAbbott$b Dean$01719101 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910812118003321 996 $aApplied predictive analytics$94116619 997 $aUNINA