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Hello,
First of all, congratulations for the eaftools library. It is one of the best tools I've seen to visualize the results of multi-objective optimization. I have three quick questions related to its use (I've searched through the documentation, the website, and the source code and did not find it):
1- Is there a way to extract to which percentile each point on the original dataset would belong (the attainment surfaces), after running the eafplot function for maximizing one criteria and minimizing the other one? Example: I've generated a plot with percentiles = c(0, 20, 40, 60, 80, 100) and I can plot the original points in the dataset on the final plot using extra.points. However, it would be very valuable to know to which "percentile class" each point belonged, so I could calculate the % of points in each "percentile class"
2- Is there an example for running the eaf for 3 dimensions?
3- Are there any visualizations planned for the library for optimization in 3 dimensions?
Thanks a lot,
Roberto
The text was updated successfully, but these errors were encountered:
Hello, First of all, congratulations for the eaftools library. It is one of the best tools I've seen to visualize the results of multi-objective optimization.
Thanks! It is nice to know somebody is using my work and find it useful.
I have three quick questions related to its use (I've searched through the documentation, the website, and the source code and did not find it): 1- Is there a way to extract to which percentile each point on the original dataset would belong (the attainment surfaces), after running the eafplot function for maximizing one criteria and minimizing the other one? Example: I've generated a plot with percentiles = c(0, 20, 40, 60, 80, 100) and I can plot the original points in the dataset on the final plot using extra.points. However, it would be very valuable to know to which "percentile class" each point belonged, so I could calculate the % of points in each "percentile class"
3- Are there any visualizations planned for the library for optimization in 3 dimensions?
Not at the moment but only because of lack of time and man (or woman) power. I would absolutely love to have 3D visualizations and ways to visualize even higher dimensions and I know quite well the literature available. But I don't have enough free time to do it myself and I haven't found people willing and capable to help with this or money to fund the work.
I would also like to convert all the visualizations to use ggplot2 and possibly plotly. I have created a proof of concept for a different project: https://zenodo.org/record/5040421 but converting the whole package and checking that everything works is too large a project for the amount of free time that I have available. Any help is very much appreciated.
Hello,
First of all, congratulations for the eaftools library. It is one of the best tools I've seen to visualize the results of multi-objective optimization. I have three quick questions related to its use (I've searched through the documentation, the website, and the source code and did not find it):
1- Is there a way to extract to which percentile each point on the original dataset would belong (the attainment surfaces), after running the eafplot function for maximizing one criteria and minimizing the other one? Example: I've generated a plot with percentiles = c(0, 20, 40, 60, 80, 100) and I can plot the original points in the dataset on the final plot using extra.points. However, it would be very valuable to know to which "percentile class" each point belonged, so I could calculate the % of points in each "percentile class"
2- Is there an example for running the eaf for 3 dimensions?
3- Are there any visualizations planned for the library for optimization in 3 dimensions?
Thanks a lot,
Roberto
The text was updated successfully, but these errors were encountered: