  Volcano eruption forecast remains a challenging and controversial problem
despite the fact that data from volcano monitoring significantly increased in
quantity and quality during the last decades.This study uses pattern
recognition techniques to quantify the predictability of the 15 Piton de la
Fournaise (PdlF) eruptions in the 1988-2001 period using increase of the daily
seismicity rate as a precursor. Lead time of this prediction is a few days to
weeks. Using the daily seismicity rate, we formulate a simple prediction rule,
use it for retrospective prediction of the 15 eruptions,and test the prediction
quality with error diagrams. The best prediction performance corresponds to
averaging the daily seismicity rate over 5 days and issuing a prediction alarm
for 5 days. 65% of the eruptions are predicted for an alarm duration less than
20% of the time considered. Even though this result is concomitant of a large
number of false alarms, it is obtained with a crude counting of daily events
that are available from most volcano observatories
