Levels Tought:
Elementary,Middle School,High School,College,University,PHD
Teaching Since: | Jul 2017 |
Last Sign in: | 210 Weeks Ago, 1 Day Ago |
Questions Answered: | 15833 |
Tutorials Posted: | 15827 |
MBA,PHD, Juris Doctor
Strayer,Devery,Harvard University
Mar-1995 - Mar-2002
Manager Planning
WalMart
Mar-2001 - Feb-2009
Deadline: Saturday 01/04/2017
Data mining and data warehousingÂ
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IT446- Data Mining and Data Warehousing |
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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. |
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1 Mark |
Learning Outcome(s): Demonstrates understanding of data cube computation techniques        |
Describe the four general optimization techniques for efficient computation of data cubes.
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1 Mark |
Learning Outcome(s): Demonstrates understanding and identification of frequent itemsetsand calculating their support value       |
Consider transaction table below to answer the following question.
TID |
Items |
T100 |
A, C, D, E |
T101 |
A, C, E |
T102 |
B, D, E, F |
T103 |
A, D, E, F |
T104 |
B, C, F |
T105 |
A, B, C, D, E |
If we set minimum support count equal to 50%, list all frequent itemsetsalongwith theirsupportcount percentage.
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1 Mark |
Learning Outcome(s): Demonstrates understanding of …………..       |
What is Association Rule? Discuss with example?
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1 Mark |
Learning Outcome(s): Demonstrates understanding of ………………..       |
What is Apriorialgorithm,discuss its advantages and disadvantages?
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