New plugin: Hardness of AutoML problem

Hi,

We often wonder how hard an AutoML problem is. Can we therefore add some metrics regarding that?
For example
* an eCDF plot for the cost distribution (i.e., a hard AutoML task should have only a few very well-performing configurations)
* uni-modal metric from the automl loss landscape paper (but evaluated on our surrogate models)
* convexity metric from the automl loss landscape paper (but evaluated on our surrogate models)

No files, tests, or entry points are identified. Start by locating the surrogate-model analysis and visualization components, then clarify the proposed cost-distribution, uni-modal, and convexity metrics and how completion would be evaluated.

Written by the indexing model from the issue text.