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Sparse omics-network regularization to increase interpretability and performance of linear classification models.
Michael Andel
Filip Masri
Jirí Kléma
Zdenek Krejcík
Monika Belickova
Published in:
BIBM (2015)
Keyphrases
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classification models
software quality classification
feature selection
training data
decision trees
sparsity regularization
sparse approximation
learning models
machine learning
structured sparsity
data sets
models built
feature set
prediction accuracy
search space
genetic algorithm
data mining
neural network