Print Email Facebook Twitter Operating characteristics for the design and optimisation of classification systems Title Operating characteristics for the design and optimisation of classification systems Author Landgrebe, T.C.W. Contributor Reinders, M.J.T. (promotor) Faculty Electrical Engineering, Mathematics and Computer Science Date 2007-12-19 Abstract In statistical pattern recognition, problems involve distinguishing of various concepts or classes, based on the development of classifiers/discriminators. These exploit discriminatory information existing in measurements originating from objects. A trained classifier results in a partitioning in measurement space, providing some separation between the various classes. In the (typical) case of class overlap, this partitioning inherently results in a trade-off between the various possible classification errors that may occur. This partitioning can be modified to adjust these trade-offs. Given class abundances, a classifier can be evaluated at a given partitioning. However, variations in the abundances leads to an altered classifier performance. These fundamental aspects behind classifier design and evaluation can be studied within the framework of classifier operating characteristics, which is the topic of this dissertation. The contents consist of a number of published/accepted journal and conference papers, contextualised into a number of chapters representing various aspects of operating characteristic analysis. First the well-known two-class operating characteristic is considered, with two new analyses that are useful in certain circumstances. Next, the extension to the elusive multiclass case is considered, showing how standard 2-class operating characteristics analyses can be extended theoretically to the multiclass case. The challenge behind the multiclass extension is shown to be of a computational nature, with the calculation size increasing exponentially with the number of classes. The primary thesis contribution is then presented, consisting of a number of approaches and philosophies that can be used to overcome the computational challenges. Of primary importance is the finding that most practical problems are such that not all dimensions of the operating characteristic interact together significantly. Next it is shown how the operating characteristic approach can be used to design classifiers in ill-defined environments. In these problems some classes may be poorly represented, and the goal of the classifier design is to protect against these unforeseen conditions. Finally, it is shown that operating characteristics can be applied to a multi-stage classifier setup, allowing for a holistic design incorporating interactions between classes, and the classifier stages. Subject receiver operator characteristicsrocoperating characteristics To reference this document use: http://resolver.tudelft.nl/uuid:4f4d4450-ac86-4adf-82e4-7ccba84faa0c ISBN 978-90-9022565-4 Part of collection Institutional Repository Document type doctoral thesis Rights (c) 2007 T.C.W. Landgrebe Files PDF its_landgrebe_20071219.pdf 2.84 MB Close viewer /islandora/object/uuid:4f4d4450-ac86-4adf-82e4-7ccba84faa0c/datastream/OBJ/view