01780oam 2200601zu 450 991051140860332120210721060839.00-553-89841-81-299-11648-5(CKB)1000000000001573(SSID)ssj0000278064(PQKBManifestationID)12070300(PQKBTitleCode)TC0000278064(PQKBWorkID)10241265(PQKB)10208745(MiAaPQ)EBC3314987(MiAaPQ)EBC6105557(Au-PeEL)EBL6105557(OCoLC)841311886(EXLCZ)99100000000000157320160829d2004 uy engurcnu||||||||txtccrCommon sense[Place of publication not identified]Bantam Dell20041 online resource (82 pages)Bantam classic Common sense Bibliographic Level Mode of Issuance: Monograph0-553-21465-9 Political scienceHistory18th centuryEarly works to 1800MonarchyPolitical scienceUnited States - GeneralHILCCRegions & Countries - AmericasHILCCHistory & ArchaeologyHILCCElectronic books.Political scienceHistoryMonarchyPolitical scienceUnited States - GeneralRegions & Countries - AmericasHistory & Archaeology320/.01/1Paine Thomas234445Gabaldon DianaPQKBBOOK9910511408603321Common sense1400657UNINA05367nam 2200685Ia 450 991014614720332120170809170521.01-282-12369-697866121236960-470-05886-20-470-74583-50-470-74582-7(CKB)1000000000719673(EBL)427914(OCoLC)437111479(SSID)ssj0000334784(PQKBManifestationID)11256939(PQKBTitleCode)TC0000334784(PQKBWorkID)10270861(PQKB)10703575(MiAaPQ)EBC427914(EXLCZ)99100000000071967320090224d2009 uy 0engur|n|---|||||txtccrApplied data mining for business and industry[electronic resource] /Paolo Giudici, Silvia Figini2nd ed.Hoboken, NJ John Wiley20091 online resource (259 p.)Description based upon print version of record.0-470-05887-0 Includes bibliographical references and index.Applied Data Mining for Business and Industry; Contents; 1 Introduction; Part I Methodology; 2 Organisation of the data; 2.1 Statistical units and statistical variables; 2.2 Data matrices and their transformations; 2.3 Complex data structures; 2.4 Summary; 3 Summary statistics; 3.1 Univariate exploratory analysis; 3.1.1 Measures of location; 3.1.2 Measures of variability; 3.1.3 Measures of heterogeneity; 3.1.4 Measures of concentration; 3.1.5 Measures of asymmetry; 3.1.6 Measures of kurtosis; 3.2 Bivariate exploratory analysis of quantitative data3.3 Multivariate exploratory analysis of quantitative data3.4 Multivariate exploratory analysis of qualitative data; 3.4.1 Independence and association; 3.4.2 Distance measures; 3.4.3 Dependency measures; 3.4.4 Model-based measures; 3.5 Reduction of dimensionality; 3.5.1 Interpretation of the principal components; 3.6 Further reading; 4 Model specification; 4.1 Measures of distance; 4.1.1 Euclidean distance; 4.1.2 Similarity measures; 4.1.3 Multidimensional scaling; 4.2 Cluster analysis; 4.2.1 Hierarchical methods; 4.2.2 Evaluation of hierarchical methods; 4.2.3 Non-hierarchical methods4.3 Linear regression4.3.1 Bivariate linear regression; 4.3.2 Properties of the residuals; 4.3.3 Goodness of fit; 4.3.4 Multiple linear regression; 4.4 Logistic regression; 4.4.1 Interpretation of logistic regression; 4.4.2 Discriminant analysis; 4.5 Tree models; 4.5.1 Division criteria; 4.5.2 Pruning; 4.6 Neural networks; 4.6.1 Architecture of a neural network; 4.6.2 The multilayer perceptron; 4.6.3 Kohonen networks; 4.7 Nearest-neighbour models; 4.8 Local models; 4.8.1 Association rules; 4.8.2 Retrieval by content; 4.9 Uncertainty measures and inference; 4.9.1 Probability4.9.2 Statistical models4.9.3 Statistical inference; 4.10 Non-parametric modelling; 4.11 The normal linear model; 4.11.1 Main inferential results; 4.12 Generalised linear models; 4.12.1 The exponential family; 4.12.2 Definition of generalised linear models; 4.12.3 The logistic regression model; 4.13 Log-linear models; 4.13.1 Construction of a log-linear model; 4.13.2 Interpretation of a log-linear model; 4.13.3 Graphical log-linear models; 4.13.4 Log-linear model comparison; 4.14 Graphical models; 4.14.1 Symmetric graphical models; 4.14.2 Recursive graphical models4.14.3 Graphical models and neural networks4.15 Survival analysis models; 4.16 Further reading; 5 Model evaluation; 5.1 Criteria based on statistical tests; 5.1.1 Distance between statistical models; 5.1.2 Discrepancy of a statistical model; 5.1.3 Kullback-Leibler discrepancy; 5.2 Criteria based on scoring functions; 5.3 Bayesian criteria; 5.4 Computational criteria; 5.5 Criteria based on loss functions; 5.6 Further reading; Part II Business case studies; 6 Describing website visitors; 6.1 Objectives of the analysis; 6.2 Description of the data; 6.3 Exploratory analysis; 6.4 Model building6.4.1 Cluster analysisThe increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications.CoveData miningBusinessData processingCommercial statisticsElectronic books.Data mining.BusinessData processing.Commercial statistics.005.74068006.312Giudici Paolo81878Figini Silvia862238MiAaPQMiAaPQMiAaPQBOOK9910146147203321Applied data mining for business and industry1924677UNINA03436oam 2200721K 450 991079052710332120190503073416.00-262-31463-0ebc3339687(CKB)2550000001123443(EBL)3339687(SSID)ssj0001003814(PQKBManifestationID)11636202(PQKBTitleCode)TC0001003814(PQKBWorkID)11038330(PQKB)11761688(StDuBDS)EDZ0000234242(MiAaPQ)EBC3339687(OCoLC)861199600(OCoLC)859383590(OCoLC)859880737(OCoLC)864822082(OCoLC)868954492(OCoLC)960996272(OCoLC)961663056(OCoLC)962568159(OCoLC)965409418(OCoLC)1055393335(OCoLC)1066648737(OCoLC)1081240061(OCoLC)1087369319(OCoLC-P)861199600(MaCbMITP)9719(Au-PeEL)EBL3339687(CaPaEBR)ebr10773246(CaONFJC)MIL525160(OCoLC)861199600(EXLCZ)99255000000112344320131021d2013 uy 0engur|n|---|||||txtccrLessons from the economics of crime what reduces offending? /edited by Philip J. Cook, Stephen Machin, Olivier Marie, and Giovanni MastrobuoniCambridge, Massachusetts :The MIT Press,[2013]1 online resource (251 p.)CESifo seminar seriesDescription based upon print version of record.0-262-01961-2 1-299-93909-0 Includes bibliographical references and index.Contents; Series Foreword; Crime Economics in Its Fifth Decade; Part I: Policy Choice and Normative Framework; 1 COPS and Cuffs; 2 Drug Prohibition and Its Alternatives; 3 Mechanism Experiments for Crime Policy; Part II: Crime as a Rational Choice; 4 What Works in Reducing Re-Offending?; 5 The Young Prisoner's Dilemma; 6 What Works in Reducing Hooliganism?; Part III: Feedback and Interactions; 7 Crime and Immigration: What Do We Know?; 8 Organized Crime, Violence, and the Quality of Politicians; 9 Centralized versus Decentralized Police Hiring in Italy and the United States10 The "Program of Integration and Management in Public Safety" in Minas Gerais, BrazilContributors; IndexReporting on research in the United States, Europe, and South America, this book discusses such topics as a cost-benefit analysis of additional police hiring, the testing of innovative policy interventions through field experiments, imprisonment and recidivism rates, incentives and disincentives for sports hooliganism and much more.CESifo Seminar SeriesCrimeEconomic aspectsCrime preventionCriminalsRehabilitationECONOMICS/GeneralSOCIAL SCIENCES/Political Science/Public Policy & LawCrimeEconomic aspects.Crime prevention.CriminalsRehabilitation.364.2/5Cook Philip J.1946-Machin StephenMarie OlivierMastrobuoni GiovanniOCoLC-POCoLC-PBOOK9910790527103321Lessons from the economics of crime3749277UNINA00806oam 2200253z- 450 991013740790332120241212220551.09781467376372146737637X(CKB)3710000000537831(EXLCZ)99371000000053783120220628c2015uuuu -u- -engVehicle Power and Propulsion Conference (VPPC), 2015 IEEEIEEE9781467376389 1467376388 2015 IEEE Vehicle Power and Propulsion Conference 2015 IEEE Vehicle Power and Propulsion Conference (VPPC)Vehicle Power and Propulsion Conference PROCEEDING9910137407903321Vehicle Power and Propulsion Conference (VPPC), 2015 IEEE2507777UNINA