Titlebook: Supervised Descriptive Pattern Mining; Sebastián Ventura,José María Luna Book 2018 Springer Nature Switzerland AG 2018 Pattern Mining.Supe

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https://doi.org/10.1007/978-3-319-98140-6Pattern Mining; Supervised Descriptive Rule Discovery; Subgroup Discovery; Contrast Sets; Emerging Patte

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Book 2018heuristics.  It provides some formal definitions and a general idea about patterns, pattern mining, the usefulness of patterns in the knowledge discovery process, as well as a brief summary on the tasks related to supervised descriptive pattern mining. It also includes a detailed description on the

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within this field.This book provides a general and comprehensible overview of supervised descriptive pattern mining, considering classic algorithms and those based on heuristics.  It provides some formal definitions and a general idea about patterns, pattern mining, the usefulness of patterns in the

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Contrast Sets,es differ significantly among sets of data under contrast. This chapter introduces therefore the contrast set mining problem as well as similarities and differences with regard to related techniques. Then, the problem is formally described and the most widely used metrics in this task are mathematic

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Emerging Patterns, timestamped datasets or extracting patterns that denote a clear difference between two disjoint features. This chapter introduces therefore the emerging pattern mining problem and describes the main differences with regard to contrast set mining. Then, the task is formally described as well as the

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Class Association Rules,ng items in data. Even when this task was generally defined for mining any type of association, it is sometimes desiderable the extraction of co-occurrences between a set of items and a specific target variable of interest. Thus, the general task is transformed into a more specific one, class associ

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