(Can help me ... please, do not include plagiarism)

 

1- Select two application areas for data mining NOT discussed in the text book and briefly discuss how data mining is being used to solve a problem (or to explore an opportunity)?.

 

2- What is Association Rule Mining? And explain how Market-basket analysis helps retail business to maximize the profit from business transactions?

 

3- Discuss k-nearest Neighbor (KNN) learning algorithm. What is the significance of the value of k in k-NN

 

4- Discuss the two estimation methods of classification-type data mining models while considering ANN as a classifier.

 

 

College of Computing and Informatics Decision Support Systems
IT445 Assignment 2
Deadline: Day 20/03/2017 @ 23:59
[Total Mark for this Assignment is 4]
Student Details:
Name:### ID:### CRN:###
Instructions:
This Assignment must be submitted on Blackboard via the allocated folder.
Email submission will not be accepted.
You are advised to make your work clear and well-presented, marks may be reduced for poor presentation.
You MUST show all your work.
Late submission will result in ZERO marks being awarded.
Identical copy from students or other resources will result in ZERO marks for all involved students.
Convert this Assignment to PDF just before submission. Pg. 1
Learning
Outcome(s):
Week5
The students will
be able to:
recognize the
wide range of
applications of
data mining.. Question One Question OneQuestion One 1 Marks Select two application areas for data mining NOT discussed in the text book
and briefly discuss how data mining is being used to solve a problem (or to
explore an opportunity)?.
Answer: Pg. 2
Learning
Outcome(s):
Week5
The students will
be able to:
Learn different
methods and
algorithms of data
mining. Question Two Question OneQuestion One 1 Marks What is Association Rule Mining? And explain how Market-basket analysis
helps retail business to maximize the profit from business transactions?
Answer: Pg. 3
Learning
Outcome(s):
Week6
The students will
be able to:
Define the
concept and
formulation of knearest neighbor
algorithm Question Three Question OneQuestion One 1 Marks Discuss k-nearest Neighbor (KNN) learning algorithm. What is the significance
of the value of k in k-NN.
Answer: Pg. 4
Learning
Outcome(s):
Week6
The students will
be able to:
Describe how
learning happens
in ANN. Question Four Question OneQuestion One 1 Marks Discuss the two estimation methods of classification-type data mining models
while considering ANN as a classifier.
Answer:

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