Extent:
Online-Ressource (xx, 303 pages)
Type of publication: Book / Working Paper
Language: English
Notes:
Includes bibliographical references (pages 285-295) and index
""Title page""; ""Copyright page""; ""Glossary of terms""; ""Part I: Data mining concept""; ""1 Introduction""; ""1.1 Aims of the Book""; ""1.2 Data Mining Context""; ""1.3 Global Appeal""; ""1.4 Example Datasets Used in This Book""; ""1.5 Recipe Structure""; ""1.6 Further Reading and Resources""; ""2 Data mining definition""; ""2.1 Types of Data Mining Questions""; ""2.2 Data Mining Process""; ""2.3 Business Task: Clarification of the Business Question behind the Problem""; ""2.4 Data: Provision and Processing of the Required Data""; ""2.5 Modelling: Analysis of the Data""
""2.6 Evaluation and Validation during the Analysis Stage""""2.7 Application of Data Mining Results and Learning from the Experience""; ""Part II: Data mining Practicalities""; ""3 All about data""; ""3.1 Some Basics""; ""3.2 Data Partition: Random Samples for Training, Testing and Validation""; ""3.3 Types of Business Information Systems""; ""3.4 Data Warehouses""; ""3.5 Three Components of a Data Warehouse: DBMS, DB and DBCS""; ""3.6 Data Marts""; ""3.7 A Typical Example from the Online Marketing Area""; ""3.8 Unique Data Marts""; ""3.9 Data Mart: Do's and Don'ts""; ""4 Data Preparation""
""4.1 Necessity of Data Preparation""""4.2 From Small and Long to Short and Wide""; ""4.3 Transformation of Variables""; ""4.4 Missing Data and Imputation Strategies""; ""4.5 Outliers""; ""4.6 Dealing with the Vagaries of Data""; ""4.7 Adjusting the Data Distributions""; ""4.8 Binning""; ""4.9 Timing Considerations""; ""4.10 Operational Issues""; ""5 Analytics""; ""5.1 Introduction""; ""5.2 Basis of Statistical Tests""; ""5.3 Sampling""; ""5.4 Basic Statistics for Pre-analytics""; ""5.5 Feature Selection/Reduction of Variables""; ""5.6 Time Series Analysis""; ""6 Methods""
""6.1 Methods Overview""""6.2 Supervised Learning""; ""6.3 Multiple Linear Regression for Use When Target is Continuous""; ""6.4 Regression When the Target is Not Continuous""; ""6.5 Decision Trees""; ""6.6 Neural Networks""; ""6.7 Which Method Produces the Best Model? A Comparison of Regression, Decision Trees and Neural Networks""; ""6.8 Unsupervised Learning""; ""6.9 Cluster Analysis""; ""6.10 Kohonen Networks and Self-Organising Maps""; ""6.11 Group Purchase Methods: Association and Sequence Analysis""; ""7 Validation and Application""; ""7.1 Introduction to Methods for Validation""
""7.2 Lift and Gain Charts""""7.3 Model Stability""; ""7.4 Sensitivity Analysis""; ""7.5 Threshold Analytics and Confusion Matrix""; ""7.6 ROC Curves""; ""7.7 Cross-Validation and Robustness""; ""7.8 Model Complexity""; ""Part III: Data mining in action""; ""8 Marketing""; ""8.1 Recipe 1: Response Optimisation: To Find and Address the Right Number of Customers""; ""8.2 Recipe 2: To Find the x% of Customers with the Highest Affinity to an Offer""; ""8.3 Recipe 3: To Find the Right Number of Customers to Ignore""
""8.4 Recipe 4: To Find the x% of Customers with the Lowest Affinity to an Offer""
ISBN: 1-306-55069-6 ; 978-1-118-76372-8 ; 978-1-306-55069-7 ; 1-306-55039-4 ; 978-1-119-97713-1
Source:
ECONIS - Online Catalogue of the ZBW
Persistent link: https://www.econbiz.de/10012670049