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Prior knowledge in the classification of biomedical data

Conference Paper
Publication Date:
2010
abstract:
Standard data analysis techniques for biomedical problems cannot take into account existing prior knowledge, and available literature results cannot be incorporated in further studies. In this work we review some techniques that incorporate prior knowledge in supervised classification algorithms as constraints to the underlying optimization and linear algebra problems. We analyze a case study, to show the advantage of such techniques in terms of prediction accuracy.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Generalized Eigenvalue Classifier; Neural Networks; Supervised classification; Support Vector Machines
List of contributors:
Guarracino, MARIO ROSARIO
Handle:
https://iris.cnr.it/handle/20.500.14243/71035
Book title:
Combining Soft Computing and Statistical Methods in Data Analysis
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