CSC 4740/6740 Data Mining Assignment 1 Solved

1. (10 points) Suppose we have the BestBuy customer data in the following table.

Customer
Age
David
46
Lisa
25
Michael
27
Susan
27
William
28
Mat
36
James
53
Kevin
27
Paul
18
Anthony
25


1.1) Please calculate the mean, median, and mode.





    2. (25 points) Suppose we have the climate data for Atlanta in the following table. Climate data for Atlanta
Month
Temperature (
℉
)
Jan
52.3


Feb
56.6


Mar
64.6


Apr
72.5


May
79.9


Jun
86.4


Jul
89.1


Aug
88.1


Sep
82.2


Oct
72.7


Nov
63.6


Dec
54.0





2.1) Please compute the five-number summary of this dataset.

2.2) Will there be outliers if we use boxplot to visualize the five-number summary? If yes, please indicate which data objects are outliers. Please briefly explain your answers.
2.3) Please visualize the data by using plot function in Matlab or some similar functions in other software. You can use any software. Based on the plotted curve, please also briefly describe the visualization result.





3. (15 points) Suppose we have the customers’ information in the following table.

Customer
David
Susan
Lisa
Profession
Manager
Manager
Programmer
Education
B.Sc.
B.Sc.
M.Sc.
Hobbies
Golf
Swimming
Swimming


3.1) Which types of attributes are there in the table?

3.2) Please compute the similarity values between “David” and “Susan”.

3.3) Please compute the similarity values between “Susan” and “Lisa”.





4. (15 points) Suppose we have the patients’ information in the following table.

Patient
Tom
Mat
Lucy
Fever
Yes
No
Yes
Cough
No
Yes
Yes
Sleepy
Yes
No
No
Headache
Yes
Yes
No
Running nose
Yes
Yes
No
Fatigue
Yes
Yes
Yes
Sweaty
Yes
No
Yes
Dizziness
Yes
Yes
Yes


4.1) Which types of attributes are there in the table?

4.2) Compute the similarity values between “Tom” and “Mat”;

4.3) Compute the similarity values between “Mat” and “Lucy”.





5. (15 points) Suppose we have the Fisher’s iris data in the following table.
Flower
A
B
C
Sepal Length
5.1
7.0
4.8
Sepal Width
3.5
3.2
3.4
Petal Length
1.4
4.7
1.9
Petal Width
0.2
1.4
0.2


Please choose one similarity measure and solve the following problems.

5.1) Which types of attributes are there in the table?

5.2) Which type of similarity measure do you choose?

5.3) Compute the similarity values between “A” and “B”;

5.4) Compute the similarity values between “B” and “C”.



    6. (15 points) Suppose we have the customer information in the loan company in the following table.

Customer
Kevin
John
Daniel
Credit Score Range
Excellent
Very good
Good
Salary Range
High
Very High
Medium
Age
Senior
Middle Age
Young


The ranking options within each attribute are provided in the following tables.

Credit Score Range


Excellent

Very good

Good

Fair

Poor

Salary Range


Very High

High

Medium

Low

Age


Senior

Middle Age

Young


6.1) Which types of attributes are there in the table?

6.1) Compute the similarity values between “Kevin” and “John”.

6.2) Compute the similarity values between “John” and “Daniel”.



    7. (5 points) Please normalize the following dataset by using the min-max normalization method. The new range should be [0, 1].

Patient
Tom
Mat
Lucy
Brian
Height (feet)
5.7
6.2
5.1
6.4