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Hello,
I am currently working on constructing an MMM model, but the media data involved is multivariate in nature. To provide some context, the media features encompass not only costs but also includ…
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**1)** Suggest extending OneR to the multivariate situation where the dependent variable is a vector for each case. For example, using the built-in `anscombe` data frame and `manova` in base R we can…
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**Describe the bug**
When clustering multivariate timeseries, KShapes returns the same cluster center for each dimension. When I generate 3-dimensional timeseries of 8 catogeries, TimeSeriesKMeans fi…
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this is my X_train shape = (200000,60,44) and y_train shape = (20000,)
and the code i used for classification is
python code:
from sktime.classification.kernel_based import RocketClassifier
fro…
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This is _por favor_. Is there any multivariate analyses in this package? I would like to have fast PCA implementation in this package.
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(I found several articles that I printed at around 2016)
- robust, RLM is only for univariate endog
- MultivariateLS has been added in #8919
- a first set of robust covariance estimators is in PR…
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Describe your proposed enhancement in detail.
Nilearn provides a very robust solution to univariate decoding w…
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Currently only univariate distributions are supported. A complete implementation would include seamless support for multivariate distributions. The only type that should be changed is the `KernelDensi…
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### Description of feature
Hi all,
me again....
Another very commonly used analysis in clinical data analysis are CoxPH models (and its great that you already implemented those!).
Most commonly…
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This looks like a really promising project and paper. Very promising results in the paper.
So -- I was testing the implementation in `./samformer_pytorch/` first using `run_demo.py` and this is…