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    di erent areas, such as data mining, machine learning, text mining, social network analysis, and information retrieval, and are often required to consult research papers to learn the state of the art of social media mining.

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    random forest overview; technical details; introductory overview. a random forest consists of a collection or ensemble of simple tree predictors, each capable of producing a response when presented with a set of predictor values. for classification problems, this response takes the form of a class membership, which associates, or classifies, a set

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    text mining involves the preprocessing of document collections (text categorization, feature/term extraction, etc.), the storage of the intermediate representations, the techniques to analyze these intermediate representations (such as distribution, analysis, clustering, trend analysis, and association rules), and visualization of the results.

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