B.Tech-INFORMATION TECHNOLOGY 7th Sem DATAWARE HOUSING AND MINING(Anna University Trichy, Tiruchi, Tamil Nadu-2009)

Part – B (3 X12 =36 Marks)

1. A database has five transactions. Let min-sup=60% and min-conf=80%

TID Items_bought
T100 {M,O,N,K,E,Y}
T200 {D,O,N,K,E,Y}
T300 {M,A,K,E}
T400 {M,U,C,K,Y}
T500 {C,O,O,K,I,E}

(a) Find all frequent itemsets using apriori and FP-growth,respectively.compare the efficiency of the two mining processes.
(b) List all of the strong association rules(with support s and confidence c)matching the following metarule, where X is a variable representing customers,and itemI denotes variables representing items(e.g., "a","b",etc.):

?x € Transaction,buys(x,item1)^buys(X,item2)=>buys(X,item3) [s,c].

2. Construct frequent pattern tree using FP growth

TID LIST OF ITEM_IDS
T100 I1,I2,I5
T200 I2,I4
T300 I2,I3
T400 I1,I2,I4
T500 I1,I3
T600 I2,I3
T700 I1,I3
T800 I1,I2,I3,I5
T900 I1,I2,I3



3. calculate the expected information gain for the following class labeled traing tuples.

Rid Age Income Student redit_rating class:buys_computer

1. youth high no fair no
2. youth high no excellent no
3. middle_aged high no fair yes
4. senior medium no fair yes
5. senior low yes fair yes
6. senior low yes excellent no
7. middle_aged low yes excellent yes
8. youth medium no fair no
9. youth low yes fair yes
10. senior medium yes fair yes
11. youth medium yes excellent yes
12. middle_aged medium no excellent yes
13. middle_aged high yes fair yes
14. senior medium no excellent no.

Earning:  ₹ 4.00/-