- Learning Data Mining with R
- Table of Contents
- Learning Data Mining with R
- Credits
- About the Author
- Acknowledgments
- About the Reviewers
- www.PacktPub.com
- Preface
- 1. Warming Up
- 2. Mining Frequent Patterns, Associations, and Correlations
- An overview of associations and patterns
- Market basket analysis
- Hybrid association rules mining
- Mining sequence dataset
- The R implementation
- High-performance algorithms
- Time for action
- Summary
- 3. Classification
- Classification
- Generic decision tree induction
- High-value credit card customers classification using ID3
- Web spam detection using C4.5
- Web key resource page judgment using CART
- Trojan traffic identification method and Bayes classification
- Identify spam e-mail and Naïve Bayes classification
- Rule-based classification of player types in computer games and rule-based classification
- Time for action
- Summary
- 4. Advanced Classification
- 5. Cluster Analysis
- 6. Advanced Cluster Analysis
- Customer categorization analysis of e-commerce and DBSCAN
- Clustering web pages and OPTICS
- Visitor analysis in the browser cache and DENCLUE
- Recommendation system and STING
- Web sentiment analysis and CLIQUE
- Opinion mining and WAVE clustering
- User search intent and the EM algorithm
- Customer purchase data analysis and clustering high-dimensional data
- SNS and clustering graph and network data
- Time for action
- Summary
- 7. Outlier Detection
- Credit card fraud detection and statistical methods
- Activity monitoring – the detection of fraud involving mobile phones and proximity-based methods
- Intrusion detection and density-based methods
- Intrusion detection and clustering-based methods
- Monitoring the performance of the web server and classification-based methods
- Detecting novelty in text, topic detection, and mining contextual outliers
- Collective outliers on spatial data
- Outlier detection in high-dimensional data
- Time for action
- Summary
- 8. Mining Stream, Time-series, and Sequence Data
- 9. Graph Mining and Network Analysis
- 10. Mining Text and Web Data
- A. Algorithms and Data Structures
- Index
Author
Bater Makhabel
Reviewers
Jason H.D. Cho
Gururaghav Gopal
Vibhav Kamath
Hasan Kurban
Commissioning Editor
Akram Husain
Acquisition Editors
Richard Gall
Owen Roberts
Content Development Editor
Govindan Kurumangattu
Technical Editors
Tanvi Bhatt
Jalasha D'costa
Pooja Nair
Siddhi Rane
Copy Editors
Roshni Banerjee
Karuna Narayanan
Vikrant Phadkay
Project Coordinator
Shipra Chawhan
Proofreaders
Ameesha Green
Sandra Hopper
Clyde Jenkins
Indexer
Mariammal Chettiyar
Graphics
Valentina D'silva
Disha Haria
Abhinash Sahu
Production Coordinator
Arvindkumar Gupta
Cover Work
Arvindkumar Gupta
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