Modified Hebbian learning for curve and surface fitting
Neural Networks
The nature of statistical learning theory
The nature of statistical learning theory
Practical Statistics for Medical Research
Practical Statistics for Medical Research
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Transductive reliability estimation for medical diagnosis
Artificial Intelligence in Medicine
NFI: a neuro-fuzzy inference method for transductive reasoning
IEEE Transactions on Fuzzy Systems
| Hi-index | 0.00 |
The paper introduces a novel dual-model classification method --- Dual-Model Classification System (DMCS). The DMCS is a personalized or transductive system which is created for every new input vector and trained on a small number of data. These data are selected from the whole training data set and they are closest to the new vector in the input space. In the proposed DMCS, two transductive fuzzy inference models are taken as the structure functions and trained with different sub-training data sets. In this paper, DMCS is illustrated on a case study: a real medical decision support problem of estimating the survival of hemodialysis patients. This personalized modeling method can also be applied to solve other classification problems.