Data mining : know it all

This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology. The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining. This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources. Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints. Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader's technical expertise and ability to implement practical solutions. Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. 9780123746290 Front cover 1 Data Mining: Know It All 4 Copyright page 5 Table of contents 6 About This Book 10 Contributing Authors 12 Chapter 1 What’s It All About? 18 1.1 DATA MINING AND MACHINE LEARNING 18 1.2 SIMPLE EXAMPLES: THE WEATHER PROBLEM AND OTHERS 24 1.3 FIELDED APPLICATIONS 37 1.4 MACHINE LEARNING AND STATISTICs 44 1.5 GENERALIZATION AS SEARCH 45 1.6 DATA MINING AND ETHICS 49 1.7 RESOURCES 51 Chapter 2 Data Acquisition and Integration 54 2.1 INTRODUCTION 54 2.2 SOURCES OF DATA 54 2.3 VARIABLE TYPES 56 2.4 DATA ROLLUP 58 2.5 ROLLUP WITH SUMS, AVERAGES, AND COUNTS 65 2.6 CALCULATION OF THE MODE 66 2.7 DATA INTEGRATION 67 Chapter 3 Data Preprocessing 74 3.1 WHY PREPROCESS THE DATA? 75 3.2 DESCRIPTIVE DATA SUMMARIZATION 78 3.3 DATA CLEANING 89 3.4 DATA INTEGRATION AND TRANSFORMATION 95 3.5 DATA REDUCTION 101 3.6 DATA DISCRETIZATION AND CONCEPT HIERARCHY GENERATION 115 3.7 SUMMARY 125 3.8 RESOURCES 126 Chapter 4 Physical Design for Decision Support, Warehousing, and OLAP 130 4.1 WHAT IS ONLINE ANALYTICAL PROCESSING? 130 4.2 DIMENSION HIERARCHIES 133 4.3 STAR AND SNOWFLAKE SCHEMAS 134 4.4 WAREHOUSES AND MARTS 136 4.5 SCALING UP THE SYSTEM 139 4.6 DSS, WAREHOUSING, AND OLAP DESIGN CONSIDERATIONS 141 4.7 USAGE SYNTAX AND EXAMPLES FOR MAJOR DATABASE SERVERS 142 4.8 SUMMARY 145 4.9 LITERATURE SUMMARY 146 RESOURCES 146 Chapter 5 Algorithms: The Basic Methods 148 5.1 INFERRING RUDIMENTARY RULES 149 5.2 STATISTICAL MODELING 153 5.3 DIVIDE AND CONQUER: CONSTRUCTING DECISION TREES 161 5.4 COVERING ALGORITHMS: CONSTRUCTING RULES 170 5.5 MINING ASSOCIATION RULES 177 5.6 LINEAR MODELS 185 5.7 INSTANCE-BASED LEARNING 193 5.8 CLUSTERING 201 5.9 RESOURCES 205 Chapter 6 Further Techniques in Decision Analysis 208 6.1 MODELING RISK PREFERENCES 208 6.2 ANALYZING RISK DIRECTLY 215 6.3 DOMINANCE 217 6.4 SENSITIVITY ANALYSIS 222 6.5 VALUE OF INFORMATION 232 6.6 NORMATIVE DECISION ANALYSIS 237 Chapter 7 Fundamental Concepts of Genetic Algorithms 238 7.1 THE VOCABULARY OF GENETIC ALGORITHMS 239 7.2 OVERVIEW 247 7.3 THE ARCHITECTURE OF A GENETIC ALGORITHM 258 7.4 PRACTICAL ISSUES IN USING A GENETIC ALGORITHM 302 7.5 REVIEW 307 7.6 RESOURCES 307 Chapter 8 Data Structures and Algorithms for Moving Objects Types 310 8.1 DATA STRUCTURES 310 8.2 ALGORITHMS FOR OPERATIONS ON TEMPORAL DATA TYPES 315 8.3 ALGORITHMS FOR LIFTED OPERATIONS 327 8.4 RESOURCES 336 Chapter 9 Improving the Model 338 9.1 LEARNING FROM ERRORS 340 9.2 IMPROVING MODEL QUALITY, SOLVING PROBLEMS 360 9.3 SUMMARY 412 Chapter 10 Social Network Analysis 414 10.1 SOCIAL SCIENCES AND BIBLIOMETRY 415 10.2 PAGERANK AND HYPERLINK-INDUCED TOPIC SEARCH 417 10.3 SHORTCOMINGS OF THE COARSE-GRAINED GRAPH MODEL 427 10.4 ENHANCED MODELS AND TECHNIQUES 433 10.5 EVALUATION OF TOPIC DISTILLATION 441 10.6 MEASURING AND MODELING THE WEB 447 10.7 RESOURCES 457 Index 460 #,Publisher:,Morgan,Kaufmann,#,Number,Of,Pages:,496,#,Publication,Date:,2008-11-21,#,ISBN-10,/,ASIN:,0123746299 #,Publisher:,Morgan Kaufmann,# Number Of Pages:,496,# Publication Date:,2008-11-21,# ISBN-10 / ASIN:,0123746299 The need for a laboratory and field manual to assist with the evaluation of juvenile skeletal material is long overdue. This resource is essential for the practising osteoarchaeologist and forensic anthropologist who requires a quick, reliable and easy-to-use reference to aid in the identification, siding and aging of juvenile osseous material. While excellent reference books on juvenile osteology are currently available, no pre-existing source adequately fills this particular niche in the market. This field manual is designed with practicality as its primary directive. Descriptions of each bone contain 1) morphological characteristics useful for identification, 2) other elements with which the bone may be confused, 2) tips for siding, 3) illustrations of varying developmental phases, 4) data useful for ageing, and 5) a summary of developmental timings. Concise, bullet-style descriptions assist with quick retrieval of information. Unique to this manual is the presentation of data collected from a variety of populations, utilizing a range of observational methods, as an alternative to providing one overall aging summary that is derived from a compilation of many individual sources. This manual provides a host of data on a variety of populations to enable the user to select the reference most applicable to their needs. The final chapter combines information from each bone to provide a summary of developmental changes occurring at different life stages to act as an immediate 'ready reckoner' for the knowledgeable practitioner. It also provides forms useful for documenting juvenile material and diagrams to help with the recognition of commingled juvenile remains. The manual is a must for anyone responsible for the evaluation of juvenile osseous material through dry bone assessment, radiographs, sonograms, and or CT scans This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology.

The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining.

This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources.

• Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints.
• Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader’s technical expertise and ability to implement practical solutions.
• Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases.