Re-pasting my comment here where it belongs as a reply:
It could be a great idea - to plot the data on 2 axes (x - html length or html size, y - processing time, if I understand this correctly). It's simple and elegant. I'll try that. It could be though that the chart will get messy with all this data points. One of the reasons I like the percentiles approach is that it makes it clear that there is a trade-off between message processing time and the number / percentage of messages we can process.
The OP likely made that comment because plotting the data is often done before the fancy machine learning as a part of the exploratory data analysis. (especially with a low number of variables!)
IanCal's comment about setting the alpha is a good one. Another easy option is to make a heatmap of 2D bin counts. Since you're using R already, you can use ggplot for this:
Agreed. Also, they don't discuss how they chose their features... It seems the problem was already solved before even applying ML to it. Maybe the example is too naive ?
Html size and html tags count was a natural choice. If it didn't work out the next step would be to try something else. You're right that it's a very naive example and that in a way it was solved before any ml was applied. The surprising part for me was that both features turned out to be interchangeable i.e. any of them could be used. I would expect html tags count to be much more accurate / reliable, etc. Another interesting part for me was the threshold. It's somewhat clear that it should be somewhere between 20 and 1 sec probably but where exactly?
