Dedication

pp v-vi

Contents

pp vii-x

Abbreviations

pp xi-xiv

Preface

pp xv-xvi

Acknowledgments

pp xvii-xviii

Part I - Preliminary Considerations

pp 1-2

1 - Introduction

pp 3-7

2 - Statistics Overview

pp 8-32

3 - Machine Learning Preliminaries

pp 33-50

4 - Traditional Machine Learning Evaluation

pp 51-80

Part II - Evaluation for Classification

pp 81-82

5 - Metrics

pp 83-127

6 - Resampling

pp 128-153

7 - Statistical Analysis

pp 154-208

Part III - Evaluation for Other Settings

pp 209-210

8 - Supervised Settings Other Than Simple Classification

pp 211-251

9 - Unsupervised Learning

pp 252-286

Part IV - Evaluation from a Practical Perspective

pp 287-288

10 - Industrial-Strength Evaluation

pp 289-307

11 - Responsible Machine Learning

pp 308-341

12 - Conclusion

pp 342-358

Appendices

pp 359-360

Appendix A - Statistical Tables

pp 361-372

Appendix B - Advanced Topics in Classification Metrics

pp 373-386

References

pp 387-402

Index

pp 403-408