PerformViz
Tome Eftimov, Rok Hribar, Urban Škvorc, Gorjan Popovski, Gašper Petelin, Peter Korošec · 2020
To visually present the overall performance of several algorithms tested on several benchmark problems on one plot, we present a machine learning approach, called performViz. It allows one to clearly see, from a single plot, which algorithms are most suited for a given problem, the influence of each problem on the overall algorithm performance and similarities among both algorithms and problems. It consists of four steps: i) selecting a performance measure, ii) selecting a statistic to calculate a representative value of the performance measure for each algorithm on each problem, iii) performing hierarchical clustering, and iv) using heatmaps to visualize the clustering result.