Veracity of big data machine learning and other approaches to verifying truthfulness
Examine the problem of maintaining the quality of big data and discover novel solutions. You will learn the four V's of big data, including veracity, and study the problem from various angles. The solutions discussed are drawn from diverse areas of engineering and math, including machine learni...
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| Format: | eBook |
| Language: | English |
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[United States]
Apress
2018
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| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Sequential Probability Ratio Test (SPRT)The CUSUM Technique; Kalman Filter; Summary; Chapter 5: Machine Learning Algorithms; The Microblogging Example; Collecting the Ground Truth; Logistic Regression; Naïve Bayes Classifier; Support Vector Machine; Artificial Neural Networks; K-Means Clustering; Summary; Chapter 6: Formal Methods; Terminology; Propositional Logic; Predicate Calculus; Fuzzy Logic; Summary; Chapter 7: Medley of More Methods; Collaborative Filtering; Vector Space Model; Summary; Chapter 8: The Future: Blockchain and Beyond; Blockchain Explained; Blockchain for Big Data Veracity
- Includes bibliographical references and index
- Intro; Table of Contents; About the Author; Acknowledgments; Introduction; Chapter 1: The Big Data Phenomenon; Why "Big" Data; The V's of Big Data; Veracity
- The Fourth 'V'; Summary; Chapter 2: Veracity of Web Information; The Problem; The Causes; The Effects; The Remedies; Characteristics of a Trusted Website; Summary; Chapter 3: Approaches to Establishing Veracity of Big Data; Machine Learning; Change Detection; Optimization Techniques; Natural Language Processing; Formal Methods; Fuzzy Logic; Information Retrieval Techniques; Blockchain; Summary; Chapter 4: Change Detection Techniques