Titlebook: Inductive Databases and Constraint-Based Data Mining; Sa?o D?eroski,Bart Goethals,Pan?e Panov Book 2010 Springer Science+Business Media, L

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A Practical Comparative Study Of Data Mining Query Languagesibility with which data mining can be performed. By integrating data mining more closely into a database querying framework, separate steps such as data preprocessing, data mining, and postprocessing of the results, can all be handled using one query language. In this chapter, we compare six existin

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A Theory of Inductive Query Answerings over monotonic and anti-monotonic predicates. Boolean inductive queries can be used to address many problems in data mining and machine learning, such as local pattern mining and concept-learning, and actually provides a unifying view on many machine learning and data mining tasks. Secondly, we de

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Constrained Predictive Clustering interested in the most compact clusters or the most accurate model; other factors, such as model size and prediction cost, may also be important.We will see how such factors can be controlled by means of constraints. In predictive clustering trees, constraints can be imposed both from the clusterin

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Inductive Querying with Virtual Mining Viewsthis chapter, we present an inductive database system in which the query language is traditional SQL. More specifically, we present a system in which the user can query the collection of all possible patterns as if they were stored in traditional relational tables. We show how such tables, or mining

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SINDBAD and SiQL: Overview, Applications and Future Developmentsuage SiQL, we present application scenarios from the areas of gene expression/regulation and small molecules. Next, we describe a web service interface to S. that enables new possibilities for inductive databases (distributing tasks over multiple servers, language and platform independence, …). Fina