Drawbacks of Apriori Algorithm and FP-Growth Analysis | Data Warehousing and Data Mining 2079

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Data Warehousing and Data Mining207910 marksNumerical: FP-growth algorithmFinding frequent itemset

Drawbacks of Apriori Algorithm and FP-Growth Analysis

Drawback 1: Generation of a huge number of candidate itemsets. Apriori generates a large number of candidate itemsets at every level. If there are $10^4$ frequent 1-itemsets, it must generate more than $10^7$ candidate 2-itemsets. To discover a long frequent pattern of size 100, roughly

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Drawback 1: Generation of a huge number of candidate itemsets. Apriori generates a large number of candidate itemsets at every level. If there are $10^4$ frequent 1-itemsets, it must generate more than $10^7$ candidate 2-itemsets. To discover a long frequent pattern of size 100, roughly