In this paper, we focus on the problem of feature selection with confidence machines (CM). CM allows us to make predictions
within predefined confidence levels, thus providing a controlled and calibrated classification environment. We present a new
feature selection method, namely Strangeness Minimisation Feature Selection, designed for CM. We apply this feature selection
method to the problem of microarray classification and demonstrate its effectiveness.