1. Consider a data set including five items ( {a, b, c, d, e} ), suppose we have the following frequent 3 item sets: ( {a, b, c},{a, b, d},{a, b, e},{a, c, d},{a, c, e},{b, c, d},{b, c, e},{c, d, e} .(20 ) points) (a) In the lecture of association analysis (Slide 23 of Chapter 5), we introduced a ( F_{k-1} imes F_{k-1} ) method for frequent itemset candidate generation. Based on the above 3-item sets, we can generate four 4-item sets using ( F_{k-1} imes F_{k-1} ) method, list these four 4-item sets ( 10 points):

1. Consider a data set including five items {a,b,c,d,e}, suppose we have the following frequent 3 item sets: {a,b,c},{a,b,d},{a,b,e},{a,c,d},{a,c,e},{b,c,d},{b,c,e},{c,d,e}.(20 points) (a) In the lecture of association analysis (Slide 23 of Chapter 5), we introduced a Fk1Fk1 method for frequent itemset candidate generation. Based on the above 3-item sets, we can generate four 4 -item sets using Fk1Fk1 method, list these four 4 -item sets ( 10 points)