This paper examines an approach for improving the accuracy of passenger show rate
predictions for airlines. The method involves the logical analysis of data. This method based
on optimization techniques, detects sets of conditions for which all the satisfying passengers
have a significantly higher or lower show rate than the studied population. The passengers
are classified according to the patterns as show, no-show or unknown. When compared to
Air Canada's current tool for overbooking forecasts, which is based on historical statistics …