Apply the Apriori algorithm to the following data set:

The set of items is {milk, bread, cookies, eggs, butter, coffee, juice}. Use 0.2 for the minimum support value.

First, we compute the support for 1-item sets
(e.g., milk appears in 5 out of the 10 transactions, support is 0.5):

1-ITEM SETS SUPPORT
milk 0.5
bread 0.4
eggs 0.4
coffee 0.3
juice 0.3
cookies 0.2
butter 0.2

The min support required is 0.2, so all 1-item sets satisfy
this requirement, i.e. they are all frequent.

For the next iteration, we examine 2-item sets composed of
the frequent 1-item sets. The number of potential 2-item sets
is 21 (i.e., 7 items taken 2 at a time). The 2-item sets that
satisfy the min support of 0.2 are the following:

2-ITEM SETS SUPPORT
milk,bread 0.4
milk,eggs 0.3
bread,eggs 0.3

For the next iteration, we examine 3-item sets composed of
the frequent 2-item sets. The 3-item sets that satisfy the
min support of 0.2 are the following:

3-ITEM SETS SUPPORT
milk,bread,eggs 0.3