On a General Transformation Making a Dissimilarity Matrix Euclidean

On a General Transformation Making a Dissimilarity Matrix Euclidean

On page 42, Table 1 should be numbered Table 3, and Table 2 should be numbered Table 4. On page 43, Table 6 should be numbered Table 1 and ordered in first position among the seven tables, Table 7 should be numbered Table 2 and ordered in second position among the seven tables, Table 3 should be numbered Table 5, Table 4 should be numbered Table 6, and Table 5 should be numbered Table 7. The Ta...

a study on rate making and required reserves determination in reinsurance market: a simulation

reinsurance is widely recognized as an important instrument in the capital management of an insurance company as well as its risk management tool. this thesis is intended to determine premium rates for different types of reinsurance policies. also, given the fact that the reinsurance coverage of every company depends upon its reserves, so different types of reserves and the method of their calc...

The dissimilarity representation for non-Euclidean pattern recognition, a tutorial

On Not Making Dissimilarities Euclidean

Non-metric dissimilarity measures may arise in practice e.g. when objects represented by sensory measurements or by structural descriptions are compared. It is an open issue whether such non-metric measures should be corrected in some way to be metric or even Euclidean. The reason for such corrections is the fact that pairwise metric distances are interpreted in metric spaces, while Euclidean d...

Non-Euclidean dissimilarity data in pattern recognition

This thesis addresses problems in dissimilarity (proximity) learning, particularly focusing on identifying the sources and rectifying the non-Euclidean dissimilarity in pattern recognition. We aim to develop a framework for analyzing the non-Euclidean dissimilarity by combining the methods from differential geometry and manifold learning theory. The algorithms are applied to objects represented...