Generalized vector spaces model in information retrieval
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Neural networks and the financial markets: predicting, combining and portfolio optimisation
Neural networks and the financial markets: predicting, combining and portfolio optimisation
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Maximal profits imply finite optimal interest rates
CI '07 Proceedings of the Third IASTED International Conference on Computational Intelligence
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The paper is motivated by a ranking problem arising e.g. in financial institutions. This ranking problem is reduced to a system of inequalities that may be solved by applying the perceptron learning theorem. Under certain additional assumptions the associated probabilities are derived by exploiting Bayes' Theorem. It is shown that from these a posteriori probabilities the original classifier may be recovered. On the other hand, assuming that perfect classification is possible, a maximum likelihood solution is derived from the classifier. Some experimental results are given.