Source code for cave.utils.tooltips

[docs]def get_tooltip(header): tooltips = { "Performance Analysis": """ Contains different ways of analyzing the final incumbent and the performance of the algorithm's default parameter configuration.""", "Default 3d": """ Projection of feature space into three dimensions, different viewpoints for enhanced explanation.""", "Incumbent 3d": """ Projection of feature space into three dimensions, different viewpoints for enhanced explanation.""", "Configurator's behavior": """ Analysis of the trajectory and the runhistory returned by a configurator to gain insights into how the configurator tried to find a well-performing configuration.""", "Parameter Importance": """ Parameter Importance analysis to determine which of the parameters most influence the analysed algorithms performance.""", "Feature Analysis": """ Analysis of the instance features to gain insights into the instance set that was used during the optimization.""", "Feature Importance": """ Reduction of the out-of-the-bag root mean squared error of the random forest empirical performance model by applying forward selection on the set of instance features. Using this method, we can identify a set of instance features that suffices to obtain prediction accuracy comparable to using the full set of features.""", } if header in tooltips: return tooltips[header] else: return False