  We consider the problem of estimating a function $f\_{0}$ in logistic
regression model. We propose to estimate this function $f\_{0}$ by a sparse
approximation build as a linear combination of elements of a given dictionary
of $p$ functions. This sparse approximation is selected by the Lasso or Group
Lasso procedure. In this context, we state non asymptotic oracle inequalities
for Lasso and Group Lasso under restricted eigenvalues assumption as introduced
in \cite{BRT}.
