Data Mining

This is the link of the book for the Assignment:

http://proquest.safaribooksonline.com/9780470526828/where_is_data_mining_used_question?readerfullscreen=&readerleftmenu=1&reader=#X2ludGVybmFsX0J2ZGVwRmxhc2hSZWFkZXI/eG1saWQ9OTc4MDQ3MDUyNjgyOC8xMzM=

Assignment:

1. 6.1, and 6.3 on page 133-134 and answer Essay Question: 

Explain the differences between statistical and machine-learning approaches to the analysis of large datasets. 

2. Chapter 7: Problems 1 and 2 on Page 146 and answer Essay Question: How does a k-Nearest Neighbor learner make predictions about new data points? How does a distance-weighted k-Nearest Neighbor learner differ from a standard k-Nearest Neighbor learner?  What is locally weighted regression? 

3. Chapter 8: Problem 1 a, b, c & d on Page 162. Special note about Chapter 8: Problem 1. Please add the following to the problem statement: Consider the following customer: Age=40, Experience=10, Income=84, Family=2, CCAvg=2, Education_2=1, Education_3=0, Mortgage=0, Securities Account=0, CD Account=0, Online=1 and Credit card = 1." This was omitted from the textbook.This week's assignment requires that you use Excel pivot tables.

4. Essay Question: Why is naive Bayesian classifier called Naive? Briefly outline the major ideas of naive Bayesian classification.

Thank you.