Robust data mining techniques with application in biomedicine and engineering

Analysis and interpretation of large datasets is a very significant problem that arises in many areas of science. The task of data analysis becomes even harder when data are uncertain or imprecise. Such uncertainties introduce bias and make massive data analysis an even more challenging task. Over the years there have been developed many mathematical methodologies for data analysis based on mathematical programming. In this field, the deterministic approach for handling uncertainty and immunizing algorithms against undesired scenarios is robust optimization. In this work we examine the application of robust optimization is some well known data mining algorithms. We explore the optimization structure of such algorithms and then we state their robust counterpart formulation.