Multivariate ROCKET on GPU (Pytorch)
I’ve spent a couple of days using ROCKET and have created a Pytorch version to overcome the lack of multivariate and GPU support.
I’ve run some tests and can confirm that GPU support really help speed up the feature creation for medium/ large datasets.
I’ve also tested my new ROCKET implementation on all 84 UCR univariate datasets and got the same results as the ones published in the paper.
And I’ve run the same code on the UCR multivariate datasets, and the results also beat the best published results by a large margin, and much faster. Here’s for example the comparison to InceptionTime (one of the best DL models for TSC):
I think you may be interested in this @hfawaz.
I’ve shared a notebook where you can learn how to use the original version of ROCKET, as well as the new Pytorch version.
Once the ROCKET features are created, you can then use any classifier you want. In the notebook I show how you can use RegressionClassifierCV (as in the paper), or integrate it with fastai, to use for example a Logistic Regression.