Efficient Mining of Frequent Patterns From Uncertain Databases Using Hierarchical Agglomerative Clustering
In many real time applications such as sensors monitoring systems, location based systems etc. data uncertainty is inherent. The uncertainty may occur as a result of evaluation errors. This uncertainty becomes a major issue while performing mining operations in the databases. Traditional mining methods are less efficient when dealing with uncertain databases. While considering uncertain databases one of the major issues is to mine frequent item sets from database. Here some algorithms which are used to perform frequent pattern mining in uncertain databases are provided.
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