Independent Component Analysis for Modelling Improvement
Ryszard Szupiluk · 2004
Abstract. A common problem encountered in such disciplines as statistics, data analysis, signal processing, data mining and time series analysis is finding a suitable model to explore existing dependencies. There are many models with different advantages and it happens that different good criteria indicate different models as an optimal solution. We need good criteria to choose the best model. But how to choose the best criterion? To avoid this disadvantage we propose an Independent Component Analysis for adopting many solutions from a large set of competitive models. Such a transformation seems to capture the essential structure of data solutions in many applications.