3 Result(s)
within
Conference Paper
Bart De Moor
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Chapter and Conference Paper
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and in vision however show that thi...
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Chapter and Conference Paper
Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging
We present an approach to learn predictive models and perform variable selection by incorporating structural information from Mass Spectral Imaging (MSI) data. We explore the use of a smooth quadratic penalty ...
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Chapter and Conference Paper
A Simple Genetic Algorithm for Biomarker Mining
We present a method for prognostics biomarker mining based on a genetic algorithm with a novel fitness function and a bagging-like model averaging scheme. We demonstrate it on publicly available data sets of g...
