Titlebook: Redescription Mining; Esther Galbrun,Pauli Miettinen Book 2017 The Author(s) 2017 Redescription mining.Alternative characterizations.Data

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Algorithms for Redescription Mining,signed on these principles. Next, we compare the different methods and discuss their relative strengths and weaknesses. Finally, we consider how to adapt the algorithms to handle cases where some values are missing from the input data.

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What Is Redescription Mining,me objects. In this chapter, we provide the basic definitions of redescription mining, including the data model, query languages, similarity measures, .-value calculations, and methods for pruning redundant redescriptions. We will also briefly cover related data analysis methods and provide a short history of redescription mining research.

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What Is Redescription Mining,inologies. In order to gain insight into the phenomenon of interest, an intuitive first task is to identify the correspondences that exist between these different aspects. This is the motivating principle behind ., a data analysis task that aims at finding distinct common characterizations of the sa

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Algorithms for Redescription Mining,n other words, we need to explore the search space consisting of query pairs from the query language, looking for those pairs that have similar enough support in the data and that satisfy the other constraints. In this chapter, we present the different methods that have been proposed to carry out th

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Applications, Variants, and Extensions of Redescription Mining,em and presenting algorithmic techniques to solve this task, we look in this chapter at some of the applications, variants, and extensions of redescription mining. We start by outlining different applications, as examples of how the method can be used in various domains. Next, we present two problem