Computational and Statistical Methods for Analysing Big Data with Applications 1st Edition by Shen Liu 0081006519 9780128037324 9780081006511

Computational and Statistical Methods for Analysing Big Data with Applications 1st Edition Shen Liu – Ebook Instant Download/Delivery ISBN(s): 0081006519, 9780128037324, 9780081006511

Product details:

• ISBN 10: 0081006519
• ISBN 13: 9780128037324, 9780081006511
• Author: Liu

Computational and Statistical Methods for Analysing Big Data with Applications begins with an overview of the era of big data. It then goes on to explain different computational and statistical methods to process big data, also introducing the ways big data is analyzed in health and medical research, and then discussing how massive training data can be used in computer vision. Final sections give details on how data from mobile devices can be collected and analyzed.

Table of contents:

1. Introduction

Abstract

1.1 What is big data?

1.2 What is this book about?

1.3 Who is the intended readership?

References

2. Classification methods

Abstract

2.1 Fundamentals of classification

2.2 Popular classifiers for analysing big data

2.3 Summary

References

3. Finding groups in data

Abstract

3.1 Principal component analysis

3.2 Factor analysis

3.3 Cluster analysis

3.4 Fuzzy clustering

Appendix

References

4. Computer vision in big data applications

Abstract

4.1 Big datasets for computer vision

4.2 Machine learning in computer vision

4.3 State-of-the-art methodology: deep learning

4.4 Convolutional neural networks

4.5 A tutorial: training a CNN by ImageNet

4.6 Big data challenge: ILSVRC

4.7 Concluding remarks: a comparison between human brains and computers

Acknowledgements

References

5. A computational method for analysing large spatial datasets

Abstract

5.1 Introduction to spatial statistics

5.2 The HOS method

5.3 MATLAB functions for the implementation of the HOS method

5.4 A case study

References

6. Big data and design of experiments

Abstract

6.1 Introduction

6.2 Overview of experimental design

6.3 Mortgage Default Example

6.4 U.S.A domestic Flight Performance – Airline Example

6.5 Conclusion

References

7. Big data in healthcare applications

Abstract

7.1 Big data in healthcare-related fields

7.2 Predicting days in hospital (DIH) using health insurance claims: a case study

Acknowledgement

References

8. Big data from mobile devices

Abstract

8.1 Data from wearable devices for health monitoring

8.2 Mobile devices in transportation

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