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The Rough Set (RS) theory can be considered as a tool to reduce the input dimensionality and to deal with vagueness and uncertainty in datasets. Over the years, there has been a rapid growth in interest in rough set theory and its applications in artificial intelligence and cognitive sciences, especially in research areas such as machine learning,… (More)
The paper below summarizes the basic methodology of association rules along with the mining association algorithms. The algorithms include the most basic Apriori algorithm along with other algorithms such as AprioriTid, AprioriHybrid and their comparison.
This paper revisits the problem of active learning and decision making when the cost of labeling incurs cost and unlabeled data is available in abundance. In many real world applications large amounts of data are available but the cost of correctly labeling it prohibits its use. In many cases, where unlabeled data is available in abundance, active learning… (More)