  Current and future large astronomical surveys will yield multiparameter
databases on millions or even billions of objects. The scientific exploitation
of these will require powerful, robust, and automated classification tools
tailored to the specific survey. Partly motivated by this, the past five to ten
years has seen a significant increase in the amount of work focused on
automated classification and its application to astronomical data. In this
article, I review this work and assess the current status of automated stellar
classification, with particular regard to its potential application to large
astronomical surveys. I examine both the strengths and weaknesses of the
various techniques and how they have been applied to different classification
and parametrization problems. I finish with a brief look at the developments
still required in order to apply a stellar classifier to a large survey.
