![]() However, beyond the issue of the negative space discussed by the authors in the conclusion, no other drawbacks or possible limitations of R2 have been discussed. ![]() The use-cases and the medical experiment cover most differences between R2 and SMAPE and truly show the benefit of using R2. The real medical scenario is interesting, but the manuscript would be much more complete if other real scenarios were included: other medical scenarios (e.g., COVID-19 cases prediction) or other real contexts (e.g., financial predictions). The experiments cover most aspects where R2 and SMAPE differ, especially the use-cases 1-5. The choice of R2 and SMAPE is well-justified based on informativeness, among all the other surveyed metrics. "deeper description of for R2" on line 122, "despite of the ranges" on line 191). Language is very good, with only some typos/mistakes to correct (e.g. Data is either provided or freely available online (Lichtinghagen dataset). Results are clearly and transparently presented. Methods and experiments are described thoroughly. Includes a thorough review of the literature, and contextualisation of the work within the state-of-the-art. The manuscript follows the defined standards.
0 Comments
Leave a Reply. |