The Analytics Edge:
"Provides a unified, insightful, modern, and entertaining treatment of analytics. The book covers the science of using data to build models, improve decisions, and ultimately add value to institutions and individuals"--Back cover
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Belmont, Massachusetts
Dynamic Ideas LLC
2016
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Summary: | "Provides a unified, insightful, modern, and entertaining treatment of analytics. The book covers the science of using data to build models, improve decisions, and ultimately add value to institutions and individuals"--Back cover |
| Item Description: | Literaturverzeichnis Seite 447-458 |
| Physical Description: | xvii, 462 Seiten Illustrationen, Diagramme, Karten 23 cm |
| ISBN: | 9780989910897 |
Staff View
MARC
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Record in the Search Index
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| adam_text | Titel: The analytics edge
Autor: Bertsimas, Dimitris
Jahr: 2016
Contents
Preface xiii
I Humans and Machines 1
1 Models Versus Experts 3
1.1 Predicting the Quality and Prices of Wine....................4
1.2 Assessing Quality in Healthcare................................8
1.3 Forecasting Supreme Court Decisions..........................11
1.4 The Competitive Edge of Models..............................17
1.5 Notes and Sources ..............................................17
2 How Do You Make a Grandmaster Blink? 19
2.1 1996 - Deep Blue vs. Garry Kasparov in Philadelphia ... 20
2.2 Lunch at IBM Research........................................21
2.3 Strategy and Decision Trees....................................22
2.4 The Anatomy of Deep Blue....................................28
2.5 Constructing Deep(er) Blue....................................29
2.6 1997 - Deep Blue vs. Garry Kasparov in New York..........30
2.7 Aftermath........................................................32
2.8 Notes and Sources ..............................................34
3 What is Watson? 37
3.1 February 14, 2011 - The Game is Afoot ......................38
3.2 Natural Language Understanding and Text Mining..........43
3.3 Deep Q A ......................................................46
3.4 The Anatomy of Watson........................................51
3.5 February 16, 2011 - Final Jeopardy............................54
3.6 What Next?......................................................57
3.7 Notes and Sources ..............................................58
vii
viii Contents
II Sports and Games 61
4 How to Evaluate Championship Players 63
4.1 The Story of Moneyball........................................64
4.2 Introduction to the NBA........................................71
4.3 Measuring Offensive and Defensive Ability....................72
4.4 The Best Players................................................79
4.5 Other Popular Rating Metrics..................................81
4.6 The Analytics Edge in Sports..................................83
4.7 Notes and Sources ..............................................84
5 Optimizing Sports League Structures 85
5.1 Road Trips, Travel, Leagues and Divisions ..................88
5.2 How Good is a League Structure?..............................89
5.3 A Fast Structure Construction Heuristic......................91
5.4 Using Integer Optimization to Optimize League Structure* 95
5.5 Results............................................................98
5.6 Conclusions......................................................102
5.7 Notes and Sources ..............................................103
6 The MIT Blackjack Team 105
6.1 The Game of Blackjack ........................................106
6.2 A Beatable Game................................................109
6.3 Data Collection..................................................117
6.4 Blackjack Today ................................................117
6.5 Notes and Sources ..............................................118
III Healthcare 121
7 The Framingham Heart Study 123
7.1 Early Misconceptions............................................124
7.2 The Beginning of the Study....................................125
7.3 The Framingham Risk Score....................................126
7.4 Other Impacts of the Study....................................135
7.5 A Different World ..............................................137
7.6 Notes and Sources ..............................................138
8 Predicting Healthcare Costs 139
8.1 Dealing with Claims Data................... 140
8.2 Methods to Predict Costs................... 145
8.3 The Results........................... 150
8.4 Autonomous Discovery of Medical Knowledge........ 153
8.5 Conclusions........................... 155
8.6 Notes and Sources ....................... 155
Contents ix
9 Medical Monitoring and Predictive Diagnosing 157
9.1 Detecting Patterns of Heart Attacks..........................158
9.2 The Artemis Project: Real-Time Analysis in the NICU . . . 164
9.3 A New Type of Physician s Assistant..........................170
9.4 Notes and Sources ..............................................170
10 Analytics for Kidney Allocation 171
10.1 Distribution and Allocation Policies ..........................172
10.2 Designing Allocation Policies..................................178
10.3 Numerical Evidence ............................................182
10.4 The Power of Analytics ........................................185
10.5 Notes and Sources ..............................................188
IV The Internet 189
11 The Heart of Google s Search Engine 191
11.1 The Growth of Google..........................................192
11.2 The PageRank Algorithm......................................194
11.3 Applications of the PageRank Algorithm......................199
11.4 The Edge of Simplicity..........................................201
11.5 Notes and Sources ..............................................201
12 How Online Advertising Changed the Internet 203
12.1 Introduction and History of Google Advertising..............204
12.2 AdWords........................................................205
12.3 Using Optimization to Create an Edge........................207
12.4 The Problem from Google s Perspective......................211
12.5 The Problem from the Advertiser s Perspective* ............215
12.6 Online Advertising in Practice ................................220
12.7 Notes and Sources ..............................................220
13 Recommendations Worth a Million 223
13.1 Getting Advice from Data......................................224
13.2 Types of Recommendation Systems............................225
13.3 Netflix............................................................229
13.4 Amazon..........................................................234
13.5 eHarmony........................................................236
13.6 The Edge of Recommendation Systems........................237
13.7 Notes and Sources ..............................................238
V Combating Crime 239
14 Fraud Detection 241
14.1 Reducing Health Care Fraud ..................................242
X
Contents
14.2 Detection and Prevention of Medical Fraud and Abuse . . . 243
14.3 Defining Peer Groups ..........................................246
14.4 The Condorcet Method ........................................250
14.5 Detecting Suspicious Behavior..................................255
14.6 A Commercial Software Offering..............................256
14.7 Verify New York................................................257
14.8 Detecting Tax Fraud and Insider Fraud ......................258
14.9 Notes and Sources ..............................................259
15 Predictive Policing 261
15.1 A Dynamic Crime Index........................................262
15.2 What Burglaries and Earthquakes Have in Common .... 270
15.3 Real Time Crime Centers......................................272
15.4 Notes and Sources ..............................................274
16 Network Science and Policing 275
16.1 Gangs and Policing in Chicago................................276
16.2 Social Networks..................................................278
16.3 Centrality........................................................280
16.4 The Social Incentive Influence Problem*......................282
16.5 A Heuristic for SI I ..............................................288
16.6 How Good is the Heuristic?....................................288
16.7 Notes and Sources ..............................................291
VI Management of Operations 293
17 Increasing Revenue with Analytics 295
17.1 The Right Strategy..............................................296
17.2 Revenue Management at
American Airlines ..............................................299
17.3 Casino Revenue Management at Harrah s Cherokee..........305
17.4 A Technique for All Industries ................................310
17.5 Notes and Sources ..............................................311
18 A Life-Saving Analytics Operation 313
18.1 The Emergency Department at BIDMC......................314
18.2 The Simulation Model..........................................315
18.3 What-if Analyses..............................................324
18.4 The Strength of Simulation.................. 329
18.5 Notes and Sources ....................... 330
Contents xi
VII Finance 331
19 An Analytical Valuation of Stock Options 333
19.1 What are Options and Why are They Important? ..........334
19.2 The Pricing of a One-Period Option..........................335
19.3 The Pricing of a Multi-Period Option ........................338
19.4 Calibration of Parameters and a Real World Example* . . . 340
19.5 Impact............................................................342
19.6 Notes and Sources ..............................................344
20 The Analytics Edge in Asset Management 345
20.1 Mutual Funds....................................................346
20.2 Alpha Models....................................................349
20.3 Portfolio Construction..........................................352
20.4 Simulation and Performance....................................358
20.5 Concluding Remarks............................................359
20.6 Notes and Sources ..............................................359
VIII Methods and Exercises to Put the Analytics
Edge into Action 361
21 Analytics Methods 363
21.1 Linear Regression................................................364
21.2 Logistic Regression..............................................368
21.3 CART and Random Forests....................................373
21.4 Clustering........................................................377
21.5 Data Visualization..............................................382
21.6 Linear and Integer Optimization..............................389
21.7 Notes and Sources ..............................................391
22 Analytics Explorations and Dives 393
22.1 Linear Regression Exercises....................................394
22.2 Logistic Regression Exercises..................................400
22.3 CART and Random Forests Exercises ........................409
22.4 Clustering Exercises ............................................414
22.5 Visualization Exercises..........................................421
22.6 Linear Optimization Exercises..................................428
22.7 Integer Optimization Exercises................................436
22.8 Notes and Sources ..............................................445
References 447
Index 459
|
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| contents | Includes bibliographical references and index |
| ctrlnum | (OCoLC)954188663 (DE-599)BVBBV043662360 |
| discipline | Informatik Soziologie Mathematik Wirtschaftswissenschaften |
| format | Book |
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| spelling | Bertsimas, Dimitris 1962- Verfasser (DE-588)170770680 aut The Analytics Edge Dimitris Bertsimas, Allison K. O'Hair, William R. Pulleyblank Belmont, Massachusetts Dynamic Ideas LLC 2016 © 2016 xvii, 462 Seiten Illustrationen, Diagramme, Karten 23 cm txt rdacontent n rdamedia nc rdacarrier Literaturverzeichnis Seite 447-458 Includes bibliographical references and index "Provides a unified, insightful, modern, and entertaining treatment of analytics. The book covers the science of using data to build models, improve decisions, and ultimately add value to institutions and individuals"--Back cover Decision making / Simulation methods Management / Simulation methods Data mining Computer simulation Computer simulation fast Data mining fast Decision making / Simulation methods fast Management / Simulation methods fast Entscheidungsprozess (DE-588)4121202-2 gnd rswk-swf Simulation (DE-588)4055072-2 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Datenanalyse (DE-588)4123037-1 s Data Mining (DE-588)4428654-5 s Entscheidungsprozess (DE-588)4121202-2 s Simulation (DE-588)4055072-2 s DE-604 O'Hair, Allison K. Verfasser (DE-588)1118378601 aut Pulleyblank, William R. Verfasser (DE-588)170461300 aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029075690&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bertsimas, Dimitris 1962- O'Hair, Allison K. Pulleyblank, William R. The Analytics Edge Includes bibliographical references and index Decision making / Simulation methods Management / Simulation methods Data mining Computer simulation Computer simulation fast Data mining fast Decision making / Simulation methods fast Management / Simulation methods fast Entscheidungsprozess (DE-588)4121202-2 gnd Simulation (DE-588)4055072-2 gnd Datenanalyse (DE-588)4123037-1 gnd Data Mining (DE-588)4428654-5 gnd |
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| title | The Analytics Edge |
| title_auth | The Analytics Edge |
| title_exact_search | The Analytics Edge |
| title_full | The Analytics Edge Dimitris Bertsimas, Allison K. O'Hair, William R. Pulleyblank |
| title_fullStr | The Analytics Edge Dimitris Bertsimas, Allison K. O'Hair, William R. Pulleyblank |
| title_full_unstemmed | The Analytics Edge Dimitris Bertsimas, Allison K. O'Hair, William R. Pulleyblank |
| title_short | The Analytics Edge |
| title_sort | the analytics edge |
| topic | Decision making / Simulation methods Management / Simulation methods Data mining Computer simulation Computer simulation fast Data mining fast Decision making / Simulation methods fast Management / Simulation methods fast Entscheidungsprozess (DE-588)4121202-2 gnd Simulation (DE-588)4055072-2 gnd Datenanalyse (DE-588)4123037-1 gnd Data Mining (DE-588)4428654-5 gnd |
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