Bin Yu is Chancellor's Distinguished Professor and Class of 1936 Second Chair in Statistics, EECS, and Computational Biology at the University of California, Berkeley, a 2006 Guggenheim Fellow, and a member of the US National Academy of Sciences and the American Academy of Arts and Sciences. Rebecca L. Barter is Research Assistant Professor in Epidemiology at the University of Utah.
Inhaltsangabe
Contents vii Acknowledgments xv Preface xvii I PART 1: AN INTRODUCTION TO VERIDICAL DATA SCIENCE 1 1 An introduction to veridical data science 3 2 The Data Science Life Cycle 23 3 Setting up your data science project 43 II PART 2: PREPARING, EXPLORING, AND DESCRIBING DATA 65 4 Data Preparation 67 5 Exploratory Data Analysis 109 6 Principal component analysis 149 7 Clustering 197 III PART 3: PREDICTION 253 8 An introduction to prediction problems 255 9 Predicting continuous responses with Least Squares 275 10 Extending the Least Squares algorithm 311 11 Predicting binary responses and logistic regression 353 12 Decision trees and random forest 403 13 Producing the final prediction results 437 14 Conclusion 473 Answers to True or False exercises 481
Contents vii Acknowledgments xv Preface xvii I PART 1: AN INTRODUCTION TO VERIDICAL DATA SCIENCE 1 1 An introduction to veridical data science 3 2 The Data Science Life Cycle 23 3 Setting up your data science project 43 II PART 2: PREPARING, EXPLORING, AND DESCRIBING DATA 65 4 Data Preparation 67 5 Exploratory Data Analysis 109 6 Principal component analysis 149 7 Clustering 197 III PART 3: PREDICTION 253 8 An introduction to prediction problems 255 9 Predicting continuous responses with Least Squares 275 10 Extending the Least Squares algorithm 311 11 Predicting binary responses and logistic regression 353 12 Decision trees and random forest 403 13 Producing the final prediction results 437 14 Conclusion 473 Answers to True or False exercises 481
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