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Solutions for machine problems and need all codes written to solve them

2 Question 1 (12 points) Based on the tiny database of 5 transactions in Table 1, use the Apriori algorithm to ﬁnd the frequent patterns with relative min sup = 0 . 6 . Purpose Get a better understanding as well as hands-on experience of the Apriori algorithm. Requirements For this question, you are required to simulate the basic Apriori algorithm and write down all intermediate as well as ﬁnal results. No programming is needed. Use the abbreviations we give you (C1, L1. ..) to denote which list you are writing about. You may use a table to contain all lists, or just write them one by one. For each itemset you write down in the L i lists, put its corresponding absolute support after it, with a colon between them, such as L 1 = { m : 4 ,... } . Do not forget to write down the actions (pruning, self-joining or db-scanning) you take to generate F1 and C2. Trans. Items 1 b,d,f,g,l 2 f,g,h,l,m,n 3 b,f,h,k,m 4 a,f,h,j,m 5 d,f,g,j,m Table 1: A tiny transaction database a. (2 0 ,L 1) List all candidate 1-itemsets (C1). What will you do to get rid of non-frequent 1-itemsets ( Choose one from pruning, self-joining and db-scanning )? List all frequent 1-itemsets (L1). b. (2 0 ,L 1) What will you do to generate all candidate 2-itemsets (C2) ( Choose one from pruning, self-joining and db-scanning )? List all itemsets in C2. c. (1 0 ,L 1) Take the same action you choose for computing L1 from C1, and list all frequent 2-itemsets (L2) computed from C2. d. (3 0 ,L 1) To generate all candidate 3-itemsets (C3) from L2, what is the extra action you need to consider besides the one you take from L1 to C2 in sub-question b ( Choose one from pruning, self-joining and db-scanning )? List all itemsets in C3. Are they all frequent?
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