Consider the following frequent 3-itemsets: {a, b, c}, {b, c, d}, {a, b, d}, {a, c,...
Consider the following frequent 3-itemsets: {a,
b, c}, {b, c, d}, {a, b, d}, {a, c, d}, {a, d, e}, {a, c, e}
Use the Fk−1 x F1 method and the Fk−1 x Fk−1 method to answer each
part.
a. List all the 4-itemsets that will be
generated by Fk−1 x F1 candidate generation method and the
4-itemsets that will be selected after the pruning step of the
Apriori algorithm.
b. List all the 4-itemsets that will be generated
by Fk−1 x Fk−1 candidate generation method and the 4-itemsets that
will be selected after the pruning step of the Apriori
algorithm.
c. Consider a new candidate generation method in
which a pair of frequent (k-1)-itemsets are merged only if the last
(k-2) items of the first one are identical to the first (k-2) items
of the second one. For example, {x,y,z} and {y,z,w} can be merged
to generated {x,y,z,w}. List all the 4-itemsets that will be
generated by this method and the 4-itemsets that will be selected
after the pruning step of the Apriori algorithm.
d. How do the two sets of results (i.e., the
candidates generated from candidate generation step and the
itemsets after the pruning step) you obtained from part (b) related
to the results you obtained from part (c).
Homework Answers
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Consider the following frequent 3-itemsets: {a,
b, c}, {b, c, d}, {a, b, d}, {a, c,...
Consider the transactional database shown in the following table. Transaction ID Items Bought T100 Plum, Apple,...
Consider the transactional database shown in the following table. Transaction ID Items Bought T100 Plum, Apple, Peach, Orange, Pear, Banana T200 Cherry, Apple, Peach, Orange, Pear, Banana T300 Plum, Mango, Orange, Pear, Kiwi, Strawberry T400 Plum, Watermelon, Avocado, Orange, Banana T500 Avocado, Apple, Orange, Lemon, Pear CONDITION: The minimum support is 60% and minimum confidence is 70%. Based on the CONDITION above, answer the following five questions. (1) Find all frequent itemsets using the Apriori algorithm. Show how the algorithm...
Language: SQL - Normalization and Functional Dependencies Part 4 Normalization and Functional Dependencies Consider the following relation R(A, B, C, D)and functional dependencies F that hold o...
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Part 4 Normalization and Functional Dependencies Consider the following relation R(A, B, C, D)and functional dependencies F that hold over this relation. F=D → C, A B,A-C Question 4.1 (3 Points) Determine all candidate keys of R Question 4.2 (4 Points) Compute the attribute cover of X-(C, B) according to F Question 43 (5 Points) Compute the canonical cover of F.Show each step of the generation according to the algorithm shown in class....
This question is for frequent pattern mining algorithm Apriori and closed pattern mining algorithm like CLOSET....
This question is for frequent pattern mining algorithm Apriori and closed pattern mining algorithm like CLOSET. Implement Apriori algorithm to mine frequent pattern from a transaction dataset Implement an algorithm to mine closed frequent pattern from the same dataset. You can either write a code to extract closed patterns from the result that you got in Part 1 or code CLOSET. Input Format The input dataset is a transaction dataset. The first line of the input corresponds to the minimum...
Table 1: Data set of market-basket transactions ansaction ID Items Bought [A, B, D, E (B, C, D (A...
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Problem 3: Consider the wireless topology below. The solid circles represent the transmission rad...
Problem 3: Consider the wireless topology below. The solid circles represent the transmission radius of nodes A and D, respectively, and the dashed circles represent the transmission range of B and C, respectively. In these problems, assume that losses only occur due to collisions. list the potential hidden terminals and exposed terminals when i) A is transmittng to B (ii) B is transmitting to A (iii) A is transmitting to C (iv) D is transmitting to HB Problem 4: Consider...
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QUESTION 9 Let X={a,b,c,d), f={(a,b),(6.a),(c,c),(d,d)}cXxX, and g={(a,m),(6,4),(c,b),(d,c)}cXxX. Find fog. a((aa),(b,d),(c,b),(d.c)) b.((a.d),(6.b),(c,a),(d.c)) c. ((a.a),(6.b),(c,c),(d,d)) d.((a.c),(b,d).(c.a),(d.b) QUESTION 10 Let X={a,b,c,d), f={(a,b),(b,a),(c,c),(d,d)}c XXX, and g={(a,d),(b,a),(c,b),(d,c)}cXXX. Find gog. a. ((a.a),(6,d),(c,b),(d,c)} b.([a,d),(6.b),(ca),(d.c)} c.{(a,a),(6.b),(c,c),(d,d)} d.((a.c),(b,d),(c,a),(d,b) QUESTION 11 What is the dominant operation in this algorithm? 1. Input the number of values n 2. Input the list of numbers x1, x2, ..., X 3. min = x 4. For i = 2 to n do 4.1. If xi < min then 4.1.1. min < x; 5. Output...
(1)A database has five transactions (T100 to T500) as shown in the table below. Let min sup-3 and...
(1)A database has five transactions (T100 to T500) as shown in the table below. Let min sup-3 and mi-conf-8090. TID 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, О. О. К. 1 ,E) items bought Find all the frequent itemset晜using Apriori algorithm. You must show the contents of Ck and Lk tables in each step (please refer to your lecture...
Language: SQL - Normalization and Functional
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Part 4 Normalization and Functional Dependencies Consider the following relation R(A, B, C, D)and functional dependencies F that hold over this relation. F=D → C, A B,A-C Question 4.1 (3 Points) Determine all candidate keys of R Question 4.2 (4 Points) Compute the attribute cover of X-(C, B) according to F Question 43 (5 Points) Compute the canonical cover of F.Show each step of the generation according to the algorithm shown in class....
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