A toolbox approach to flexible and efficient data mining This paper describes a flexible and efficient toolbox based on the scripting language Python, capable of handling common tasks in data mining. Using either a relational database or flat files the toolbox gives the user a uniform view of a data collection. Two core features of the toolbox are caching of database queries and parallelism within a collection of independent queries. Our toolbox provides a number of routines for basic data mining tasks on top of which the user can add more functions - mainly domain and data collection dependent - for complex and time consuming data mining tasks.
References in zbMATH (referenced in 2 articles , 1 standard article )
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- Peña, José M.; Crespo, F. Javier; Menasalvas, Ernestina; Robles, Victor: Parallel data mining experimentation using flexible configurations (2002)
- Nielsen, Ole M.; Christen, Peter; Hegland, Markus; Semenova, Tatiana; Hancock, Timothy: A toolbox approach to flexible and efficient data mining (2001)