Mark04

Posted on February 13, 2017

Marketing Management Help 04

Ques #1
 
Given the following Sales data in sales table. It consists of six products (Apples, Shampoo, Napkins, Coffee, Soap, Toothpaste) and each transaction has at the most 2 products implying there are no combination of 3 products.
 
Assume a threshold level of 2 and 75% confidence requirement.
 
Hint: while counting make sure to look at both columns. Example some purchases maybe Apples, shampoo or toothpaste, Apples
 
Apples must be counted in both columns
Sales data
Ctrl+ click
 
a. Perform apriori analysis and provide the confidence that a customer will buy toothpaste given they have already bought shampoo. Is this rule acceptable?
 
b. Provide the confidence that a customer will buy Toothpaste given they have already bought soap. Is the rule acceptable?
 
c. Provide all acceptable rules at 75% confidence
 
 

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Ques#2.
 
Given the following ownership data for Tractors based on income level and lot size
(similar example that we did in class but NOT the same)
 
Tractor_data
 
Ctrl+ click
 
Develop a two level split decision tree using
 
First level split at lot size = 19
 
Second level split follow following rule
 
If lot size > 19 AND income <= 75.5 etc..
If lot size<=19 AND income <= 65.8 etc..
 
Do not worry about third level splits
 
After developing decision tree calculate
 
Gini index
 
a. Before the split
 
b. After the first split (size =19)
 
c. After the second level splits
 
Q3 Given the following
 
Given the following Table with training Records with their actual class and the probability of them being class 1 members estimated by a classifier. Where 1 denotes a customer will buy washer/dryer and 0 implies they will not.
(source Shmueli etc)
Probability of class 1    Actual Class
0.9950                                 1
0.9875                                 1
0.9844                                 1
0.9804                                 1
0.9481                                 0
0.8893                                 1
0.8476                                 1
0.7628                                 0
0.7070                                 1
0.6807                                 1
0.6563                                  1
0.6224                                 0
0.5050                                  0
0.4713                                   1
0.3371                                    1
0.2179                                    0
0.1992                                    0
0.1494                                    0
0.0478                                    1
0.0383                                     1
0.0248                                    0
0.0218                                     0
0.0161                                      0
0.0035                                     0
 
a. Draw a “lift” chart for a person buying a washer and dryer (1) using the above model and provide the lift value for 10 cases of 1.
 
Q4. Given the following decision tree
As noted in class split values are arbitrary in the example. In real situation an algorithm will define split

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