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DM Methodology

• Introduction
• DM Process
• Problem Understanding
• Data Understanding
• Data Preparation
• Modelling
• Evaluation of results
• Deployment of results



• DM Modelling techniques
• DM Applications & References
• Glossary of terms

Modelling techniques

Modelling techniques come from fields of machine learning, signal processing, evolutionary computing and statistics. Techniques are one thing that makes data mining so specific. Modelling techniques in data mining have also one important characteristic - they au tomaticaly generate new propositions (models), about relations among important variables in the data, which is an added value to traditional confirmatory statistical analyses. Due to the essential impact that modelling techniques have on DM process, in the table bellow you will find links to parts of the tutorial devoted to more thorough presentation of basic features of data mining modelling techniques and their application.

Common structure of DM modelling techniques Model representation Estimation criteria Search method Description of DM modelling techniques Decision trees Rule Induction Methods Association Rules Clustering Methods Neural Networks ILLM Rule Induction system Evaluation of generated models Detailed description of evaluation measures and techniques for evaluating classifier models.

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© 2001 LIS - Rudjer Boskovic Institute
Last modified: January 16 2006 10:47:09.