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This paper provides an overview of data mining approaches with applications to brain disorder identification, which have attracted increasing attention in both data mining and neuroscience communities in recent years.
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"Brief overview of data-mining techniques used" section describes the brief overview of data-mining techniques that are used.
This is followed by a brief overview of related work, illustrating the power and opportunities of data mining, from sources that are not necessarily related to epidemic modeling.
This paper therefore aims to provide a comprehensive overview of existing data mining techniques and related tools and to illustrate the potential of data mining for different research areas by means of example applications.
The social impacts of data mining are discussed, including ubiquitous and invisible data mining, and privacy-preserving data mining.
Additionally, task-driven data mining concepts and principles are elaborated with the help of data mining concepts and techniques.
The mining of frequent itemsets is a fundamental and important task of data mining.
Temporal data mining is the application of data mining techniques to data that takes the time dimension into account.
After months of data mining the consultants concluded: not really.
Utility mining has recently been an emerging topic in the field of data mining.
Due to the nature of data mining, it always was.
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