Acceso restringido con credenciales UPSA.
Tutorial de uso xebook

Tabla de Contenidos: “…Preface to the Second Edition xiii -- Preface to the First Edition xv -- 1 DATA-MINING CONCEPTS 1 -- 1.1 Introduction 1 -- 1.2 Data-Mining Roots 4 -- 1.3 Data-Mining Process 6 -- 1.4 Large Data Sets 9 -- 1.5 Data Warehouses for Data Mining 14 -- 1.6 Business Aspects of Data Mining: Why a Data-Mining Project Fails 17 -- 1.7 Organization of This Book 21 -- 1.8 Review Questions and Problems 23 -- 1.9 References for Further Study 24 -- 2 PREPARING THE DATA 26 -- 2.1 Representation of Raw Data 26 -- 2.2 Characteristics of Raw Data 31 -- 2.3 Transformation of Raw Data 33 -- 2.4 Missing Data 36 -- 2.5 Time-Dependent Data 37 -- 2.6 Outlier Analysis 41 -- 2.7 Review Questions and Problems 48 -- 2.8 References for Further Study 51 -- 3 DATA REDUCTION 53 -- 3.1 Dimensions of Large Data Sets 54 -- 3.2 Feature Reduction 56 -- 3.3 Relief Algorithm 66 -- 3.4 Entropy Measure for Ranking Features 68 -- 3.5 PCA 70 -- 3.6 Value Reduction 73 -- 3.7 Feature Discretization: ChiMerge Technique 77 -- 3.8 Case Reduction 80 -- 3.9 Review Questions and Problems 83 -- 3.10 References for Further Study 85 -- 4 LEARNING FROM DATA 87 -- 4.1 Learning Machine 89 -- 4.2 SLT 93 -- 4.3 Types of Learning Methods 99 -- 4.4 Common Learning Tasks 101 -- 4.5 SVMs 105 -- 4.6 kNN: Nearest Neighbor Classifi er 118 -- 4.7 Model Selection versus Generalization 122 -- 4.8 Model Estimation 126 -- 4.9 90% Accuracy: Now What? …”