Maciej Zieba — новинки

This book concentrates on the problem of credit assignment. The goal of this work is to propose ensemble classification method, which can be applied to solve credit decisions problems. The method uses switching class labels techniques to construct complex classification system, which solves two of typical data mining problems observed in financial data mining field: the problem of imbalanced data and the problem of asymmetric cost matrix. The performance of the proposed solution is going to be evaluated on German Credits dataset.

The problem of pattern recognition is one of key issues in machine learning field. Various methods were proposed in literature depending on issues of the problem. In this work the concept of multistage neural networks is going to be presented. This approach is extension of multistage identification. The possibility of using this type of structure for pattern recognition would be discussed and examined with chosen problem from field area. Two-stage writer recognition is going to be considered as practical example in the work. Experiments using well known repository dataset are going to be made to evaluate proposed two-stage approach. On second stage iconic gesture is going to be recognized and on first stage writer is going to be identify in way determined by second stage output. The results of experiment would be confront with other possible methods used for the problem. Possible further directions of the work would be described at the end.