Comparative Analysis of Algorithms for Mining Frequent Patterns
Keywords:
Growth Algorithm, Data mining, frequent pattern mining, Apriori, FP-growthAbstract
In the computerized world, everything is moving online, and data comes in different shapes and sizes and is collected in different ways. By using data mining, frequent patterns in the databases can be identified, and it can be used in numerous applications. Finding frequent patterns in huge databases is important because it reveals important information that cannot be found through simple data surfing. To find common patterns, a variety of methods are utilized, each of which performs differently. The fundamental methods used in frequent pattern mining are Apriori and FP-growth. The functioning and experimental results of various algorithms are compared in this study, and their benefits and drawbacks are discussed.
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