Hi,
>From the doc, I have not found a sampling class.
To train a gaussian process for example, It is preferable to use sampling
techniques (low discrepancy sequences, uniform designs, etc.).
Do you plan to do such a thing?
Also, I was wondering if you were planning to add variance analysis (Sobo
Hi everyone,
I have some code that allows to upgrade (or downgrade) a PCA with a new
sample.
The update part is handy when you are doing live observations for instance
and you want a quick way to update your PCA without having to recompute the
whole thing from scratch.
Are you interested in this?
I have no idea about the comparison with
sklearn.decomposition.IncrementalPCA.
Was not aware of this but from the code it seems to be a different approach.
I will try to come with some numbers.
Pamphile
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n_features))
itime = time.time()
[pod._update(snap.T[:, None]) for snap in snapshot3]
print(time.time() - itime)
itime = time.time()
ipca.partial_fit(snapshot3)
print(time.time() - itime)
np.allclose(ipca.singular_values_[:999], pod.S[:999])
2018-07-03 11:06 GMT+02:00 Pamphile Roy :
> I h
Hi,
Is there a wish to have sensitivity analysis?
Currently we can measure the quality of a regressor’s output with a metric, but
there is nothing to on the parameter side.
It would be handy to have sensitivity measures of the input parameters on the
output. Namely: Sobol’ indices (most used).
Sorry, but these images are not mine and not from any company I have
belonged to. Good luck in finding out who they belong to.
Roy Marsten
On Mon, Mar 4, 2024 at 3:17 AM Gael Varoquaux
wrote:
> Dear Rosita,
>
> The first image is not be us, but by datacamp, so I cannot comment on it.