Kenkoooo's AtCoder problem recommendation has columns for solve probability and median solve time. I understand that solve probability is computed using the user's internal Elo, but how does kenkoooo estimate median solve time?
# | User | Rating |
---|---|---|
1 | tourist | 3985 |
2 | jiangly | 3814 |
3 | jqdai0815 | 3682 |
4 | Benq | 3529 |
5 | orzdevinwang | 3526 |
6 | ksun48 | 3517 |
7 | Radewoosh | 3410 |
8 | hos.lyric | 3399 |
9 | ecnerwala | 3392 |
9 | Um_nik | 3392 |
# | User | Contrib. |
---|---|---|
1 | cry | 169 |
2 | maomao90 | 162 |
2 | Um_nik | 162 |
4 | atcoder_official | 161 |
5 | djm03178 | 158 |
6 | -is-this-fft- | 157 |
7 | adamant | 155 |
8 | awoo | 154 |
8 | Dominater069 | 154 |
10 | luogu_official | 150 |
Kenkoooo's AtCoder problem recommendation has columns for solve probability and median solve time. I understand that solve probability is computed using the user's internal Elo, but how does kenkoooo estimate median solve time?
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You can try to read the source code: github.com/kenkoooo/AtCoderProblems
In particular, the solve time is computed here in atcoder-problems-frontend/src/utils/ProblemModelUtil.ts, which seems like a linear function of your rating times
problemModel.slope
plusproblemModel.intercept
. These two parameters are computed from a simple linear regression on participants' ratings and their solve time of the problem, not particularly sure about this but you can take a look at the time-estimator folder and function.py.