An Efficient Pattern Growth Approach for Mining Fault Tolerant Frequent Itemsets

•Mining fault tolerant (FT) frequent itemsets are computationally expensive.•Related algorithms are Apriori-like candidate generation-and-test approaches.•Apriori-like algorithms generate exponential number of candidate itemsets.•We propose mining FT frequent itemsets using frequent pattern growth approach.•The proposed approach mines complete set of itemsets with less computational cost.