Wardz….

For example, let s = {asparagus, beans, squash} from F3. The proper subsets of s are {asparagus}, {beans}, {squash}, {asparagus, beans}, {asparagus, squash}, {beans, squash}. For the first association rule shown in Table 10.5, we let ss = {asparagus, beans}, so that (s ss) = {squash}.We consider the rule R: {asparagus,
beans} ? {squash}. The [...]

C3 is then pruned, using the a priori property. For each itemset s in C3, its size k ? 1 subsets are generated and examined. If any of these subsets are not frequent, s cannot be frequent and is therefore pruned. For example, let s = {asparagus, beans, squash}. The subsets of size k ? [...]

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Consider the set of transactions D represented in Table 10.1. How would the a priori algorithm mine association rules from this data set? Let  = 4, so that an itemset is frequent if it occurs four or more times in D.We first find F1, the frequent 1-itemsets, which represent simply the individual vegetable items [...]