'Data mining' refers to a broad class of activities that have in common, a search over different ways to process or …. We characterize three attitudes toward data mining: first, that it is to be avoided and, if it is engaged in, that … and considerations of epistemic warrant and, reaches an unnecessarily hostile attitude toward data mining. The second …

characterized as data mining, in an attempt to distinguish between the problematic and the non-problematic cases. The key for this … distinction is provided by the notion of error-statistical severity. It is argued that many unwarranted data mining activities … (PR) approach to empirical modelling, it is argued that the unwarranted cases of data mining can often be avoided by …

This survey of the symposium papers argues that the problem of data mining should be of interest to both practicing … on recent work in the philosophy of science to point to parallels between data mining and practices engaged in routinely … by experimental scientists. These suggest that data mining might be seen in a more positive light than conventional …

volumes of data, data mining (DM) techniques are needed. Organizations are starting to realize the importance of data mining …

, coefficient of variation and significant mean. Data mining paradigms based on a loosely coupled neural network or alternatively a …

Hoover and Perez (1999) advocate a constructive approach to data mining. The current paper identifies four pejorative … senses of data mining and shows how Hoover and Perez?s approach counters each. To assess the benefits of constructive data … mining, the current paper applies a data-mining algorithm similar to Hoover and Perez?s to a dataset for Venezuelan consumers …

patterned after Lovell's (1983) study of data mining. The algorithm is assessed for its ability to recover the data …