IT 446
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Question One |
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Assignment #3
Deadline: Saturday 02/12/2017 @ 23:59
[Total Mark for this Assignment is 5]
Data Mining and Data Warehousing
IT 446
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.
Student Details:
Name:###
CRN:###
ID:###
College of Computing and Informatics
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Question One
1 Mark
Learning Outcome(s):
LO-2,3
a. Q1. Data objects may belong to more than one class at a time. In such cases it is difficult to assess classification accuracy. Mention your comment on what criteria you would use to compare different classifiers modeled using the same data.
b. Answer:
Question Two
1.5 Marks
Learning Outcome(s):
LO- 2, 3
c. a) Classify the following classification techniques to either eager or lazy classification.
d.
e. Decision tree, case-based reasoning, Bayesian, neural network, k-mean, k-nearest neighbor.
f.
g. b) Compare and contrast Eager and Lazy classification methods.
h. Answer:
Question Three
1.5 Marks
Learning Outcome(s):
LO-2, 3
a) Explain dendrogram. What could be the possible reason(s) for producing two different dendrograms using agglomerative clustering algorithm for the same dataset?
b) In which cases K-Means clustering algorithm fails to give good results?
Answer:
Question Four
1 Mark
Learning Outcome(s):
LO-3
a) What are the advantages of DBSCAN clustering algorithm?
b) Assume, you want to cluster observations into 3 clusters using K-Means clustering algorithm. After first iteration three clusters (C1, C2, C3) have the following observations:
C1: {(4,4), (5,5), (6,6)}
C2: {(0,6), (4,6)}
C3: {(3,9), (11,11)}
Find the cluster centroid of each cluster?
Answer:
Learning Outcome(s):