Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Sim_bm having the same final results #4

Open
HxyScotthuang opened this issue Dec 13, 2022 · 1 comment
Open

Sim_bm having the same final results #4

HxyScotthuang opened this issue Dec 13, 2022 · 1 comment

Comments

@HxyScotthuang
Copy link

Hi, I have downloaded the library and run the given example for simple Brownian motion. The results seem to be puzzling as all the statistical output for 4 different interpolation methods have the exact same training and testing accuracy as well as standard deviation.

I assume there might be some error in printing the results. The rest is fine. The final statistic part of output is as follows:

[100, 4096, 10, 256]
Train Accuracy: 0.8145344853401184
Test Accuracy: 0.8037109375
[100, 4096, 10, 256]
Train Accuracy: 0.8245442509651184
Test Accuracy: 0.8294270634651184
[100, 4096, 10, 256]
Train Accuracy: 0.822265625
Test Accuracy: 0.8216145634651184
[100, 4096, 10, 256]
Train Accuracy: 0.824462890625
Test Accuracy: 0.822265625
[100, 4096, 10, 256]
Train Accuracy: 0.8116047978401184
Test Accuracy: 0.8108723759651184
Mean train: 0.8194824457168579, Mean test: 0.817578136920929
s.d. train: 0.005379822105169296, s.d. test: 0.009120622649788857
[100, 4096, 10, 256]
Train Accuracy: 0.8145344853401184
Test Accuracy: 0.8037109375
[100, 4096, 10, 256]
Train Accuracy: 0.8245442509651184
Test Accuracy: 0.8294270634651184
[100, 4096, 10, 256]
Train Accuracy: 0.822265625
Test Accuracy: 0.8216145634651184
[100, 4096, 10, 256]
Train Accuracy: 0.824462890625
Test Accuracy: 0.822265625
[100, 4096, 10, 256]
Train Accuracy: 0.8116047978401184
Test Accuracy: 0.8108723759651184
Mean train: 0.8194824457168579, Mean test: 0.817578136920929
s.d. train: 0.005379822105169296, s.d. test: 0.009120622649788857
[100, 4096, 10, 256]
Train Accuracy: 0.8145344853401184
Test Accuracy: 0.8037109375
[100, 4096, 10, 256]
Train Accuracy: 0.8245442509651184
Test Accuracy: 0.8294270634651184
[100, 4096, 10, 256]
Train Accuracy: 0.822265625
Test Accuracy: 0.8216145634651184
[100, 4096, 10, 256]
Train Accuracy: 0.824462890625
Test Accuracy: 0.822265625
[100, 4096, 10, 256]
Train Accuracy: 0.8116047978401184
Test Accuracy: 0.8108723759651184
Mean train: 0.8194824457168579, Mean test: 0.817578136920929
s.d. train: 0.005379822105169296, s.d. test: 0.009120622649788857
[100, 4096, 10, 256]
Train Accuracy: 0.8145344853401184
Test Accuracy: 0.8037109375
[100, 4096, 10, 256]
Train Accuracy: 0.8245442509651184
Test Accuracy: 0.8294270634651184
[100, 4096, 10, 256]
Train Accuracy: 0.822265625
Test Accuracy: 0.8216145634651184
[100, 4096, 10, 256]
Train Accuracy: 0.824462890625
Test Accuracy: 0.822265625
[100, 4096, 10, 256]
Train Accuracy: 0.8116047978401184
Test Accuracy: 0.8108723759651184
Mean train: 0.8194824457168579, Mean test: 0.817578136920929
s.d. train: 0.005379822105169296, s.d. test: 0.009120622649788857

@jambo6
Copy link
Owner

jambo6 commented Dec 14, 2022

I've had a look at the code and cant immediately see why the results should be the same. @lingyiyang any thoughts?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants