TY  - BOOK
AU  - Shmueli, Galit
AU  - Bruce, Peter C.
AU  - Yahav, Inbal
AU  - Patel, Nitin R.
AU  - Lichtendahl, Kenneth C.
TI  - Data Mining for Business Analytics: Concepts, Techniques and Applications in R
SN  - 9781118879368
U1  - 658.40380 
PY  - 2018///
CY  - Hoboken
PB  - John Wiley & Sons, Inc.
KW  - Business mathematics - Computer programs
N1  - Part I: Preliminaries
1. Introduction
2. Overview of the data mining process

Part II: Data Exploration and Dimension Reduction
3. Data visualization
4. Dimension reduction

Part III: Performance Evaluation
5. Evaluating predictive performance

Part IV: Prediction and Classification Methods
6. Multiple linear regression
7. k-Nearest Neighbors (kNN)
8. The Naive Bayes classifier
9. Classification and regression trees
10. Logistic regression
11. Neural nets
12. Discriminant analysis
13. Combining methods : ensembles and uplift modeling

Part V: Mining Relationships Among Records
14. Association rules and collaborative filtering
15. Cluster analysis

Part VI: Forecasting Time Series
16. Handling time series
17. Regression-based forecasting
18. Smoothing methods

Part VII: Data Analytics
19. Social network analytics
20. Text mining

Part VIII: Cases
21. Cases

ER  -