Robust and optimal control
Matrix analysis and applied linear algebra
Matrix analysis and applied linear algebra
Prediction of Sequential Values for Debt Recovery
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
IEEE Transactions on Knowledge and Data Engineering
Pattern Recognition & Matlab Intro
Pattern Recognition & Matlab Intro
Data reduction for instance-based learning using entropy-based partitioning
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study
IEEE Transactions on Evolutionary Computation
Hi-index | 0.00 |
Machine learning and data mining algorithms usually assume that the training and future data have the same distribution and come from the same feature space. However, in majority of real-world problems, this is not true. In case of Debt portfolio appraisal we have sufficient training data only in another domain of interest, namely in other portfolios. Therefore, only knowledge transfer from these portfolios in inference for new one is possible. In the paper we propose transfer learning and learning based on similarity methods, basing on similarity between training and testing datasets. The proposed approach is examined in real domain debt portfolio valuation.