[MRG] Accelerate example plot_kernel_ridge_regression.py #21794

lisacsn · 2021-11-26T10:39:08Z

Reference Issues/PRs

References #21598

What does this implement/fix? Explain your changes.

Speed up ../examples/miscellaneous/plot_kernel_ridge_regression.py by reducing the number of samples from 10000 to 7000 for X, and 100000 to 70000 for X_plot.

Output before the changes:

And after:

Any other comments?

/

ogrisel · 2021-11-26T13:53:18Z

The text of the analysis of the prediction time is wrong. Currently it reads:

However, prediction of 100000 target values is more than tree times faster with SVR since it has learned a sparse model using only approx. 1/3 of the 100 training datapoints as support vectors.

But both on the main branch with 100k samples and in your PR with 70k samples, the KRR model predicts faster. So we could fix the text to be something like:

The speed of prediction of SVR could in theory be 3x faster than KRR because SVR uses approximately 1/3 of the 100 training datapoints as support vectors. However here we observe that this not the case, probably because of implementations details (the SVR prediction code does not seem to be as well optimized as the KRR prediction code).

and reduce the prediction set to 10k samples instead (large enough to measure a timing that is not too noisy but small enough to make this example run significantly faster).

lisacsn · 2021-11-28T10:21:51Z

Thank you for your comments.

If we reduce the prediction set to 10k samples we now have this outputs:

SVR complexity and bandwidth selected and model fitted in 0.801 s
KRR complexity and bandwidth selected and model fitted in 0.428 s
Support vector ratio: 0.290
SVR prediction for 10000 inputs in 0.029 s
KRR prediction for 10000 inputs in 0.069 s

thomasjpfan

Thanks for the PR!

thomasjpfan · 2022-04-15T17:05:59Z

examples/miscellaneous/plot_kernel_ridge_regression.py

@@ -125,7 +127,7 @@
 plt.figure()

 # Generate sample data
-X = 5 * rng.rand(10000, 1)
+X = 5 * rng.rand(7000, 1)


The final point on the graph is 10**4 because of:

sizes = np.logspace(1, 4, 7).astype(int)

below. If we want the final point to end with 10**4, then I think we need to keep this at 10000.

cmarmo · 2022-08-02T20:16:47Z

plot_kernel_ridge_regression.py has been accelerated in #21791.
I'm closing this pull request.

Accelerate example plot_kernel_ridge_regression

e863ce1

lisacsn force-pushed the accelerate_kernel_ridge_regression branch from 15f3d96 to e863ce1 Compare November 28, 2021 10:19

adrinjalali mentioned this pull request Nov 29, 2021

Accelerate slow examples #21598

Closed

41 tasks

adrinjalali changed the title ~~[MRG] Accelerate example plot_kernel_ridge_regression~~ [MRG] Accelerate example plot_kernel_ridge_regression.py Nov 29, 2021

thomasjpfan reviewed Apr 15, 2022

View reviewed changes

thomasjpfan added Stalled Documentation labels Jul 20, 2022

cmarmo removed the Stalled label Aug 2, 2022

cmarmo closed this Aug 2, 2022

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

[MRG] Accelerate example plot_kernel_ridge_regression.py #21794

[MRG] Accelerate example plot_kernel_ridge_regression.py #21794

[MRG] Accelerate example plot_kernel_ridge_regression.py #21794

[MRG] Accelerate example plot_kernel_ridge_regression.py #21794

Conversation

Reference Issues/PRs

What does this implement/fix? Explain your changes.

Any other comments?

Choose a reason for hiding this comment

Choose a reason for hiding this comment