Details

Autor(en) / Beteiligte

• Campos, M.M.
• Stengard, P.J.
• Milenova, B.L.

Titel

Data-centric automated data mining

Ist Teil von

• Fourth International Conference on Machine Learning and Applications (ICMLA'05), 2005, p.8 pp.

Ort / Verlag

IEEE

Erscheinungsjahr

2005

Quelle

IEEE

Beschreibungen/Notizen

• Data mining is a difficult task. It requires complex methodologies, including problem definition, data preparation, model selection, and model evaluation. This has limited the adoption of data mining at large and in the database and business intelligence (BI) communities more specifically. The concepts and methodologies used in data mining are foreign to database and BI users in general. This paper proposes a new approach to the design of data mining applications targeted at these user groups. This approach uses a data-centric focus and automated methodologies to make data mining accessible to nonexperts. The automated methodologies are exposed through high-level interfaces. This hides the data mining concepts away from the users thus helping to bridge the conceptual gap usually associated with data mining. We illustrate the approach with two applications: the new Oracle Predictive Analytics feature of Oracle Database 10g Release 2 and the Oracle Spreadsheet Add-In for Predictive Analytics.