Fig 8. Improvement over ridge in zero- and low-noise conditions.

This figure illustrates performance of the gridge algorithms divided by plain ridge in the same condition. The third group compares query string gridge models against topic ridge. Boxes plot the median with first and third quartiles, and the whiskers show the maximum and minimum. Each box-and-whiskers summarizes 12 data points. For the two error metrics, increasing the importance of deceptiveness through quadratic gridge yields increasing improvement over plain ridge, but the trend ends at quartic gridge. Notably, this is true even when comparing query string models (which are completely automatic) against topic ridge (which requires lots of manual attention), suggesting that deceptiveness information can be used to replace expensive human judgement. Hit rate, however, seems to gain limited benefit from deceptiveness in this experiment.