The paper presents and compares the data mining techniques for selection of the diagnostic features in the problem of blood cell recognition in leukemia. Different techniques are c...
The problem of selecting the best system from a finite set of alternatives is considered from a Bayesian decision-theoretic perspective. The framework presented is quite general,...
Background: Normalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introdu...
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
The paper addresses methods for parameter sensitivity analysis in a large, nonlinear, mechanistic model which is to be run in an online estimation scheme. The parameter sensitivit...