Feature
selection methods for mining bio-informatics data
Bontempi G,
Haibe-Kains B
The use of
data mining techniques in bioinformatics is continuously confronted
with the problem of managing datasets where the number of features is
much larger than the number of samples (high feature-to-sample ratio
datasets). The talk will first discuss some examples (from inference of
regulatory networks to discrimination in cancer classification) and
then will focus on some issues to be be taken into account for
effectively dealing with this type of data.