Is there a way to apply arbitrary preprocessing to a 3D dataset? #1492
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I see that the TimeSeriesScaler applies sklearn's Is there an aeon-thonic way to apply arbitrary preprocessing functions to an arbitrarily subsets of channels? I'm envisioning something like sklearn's ColumnTransformer but for each timeseries in a 3D dataset. I tried looking through the code, but I hit a cognitive wall with regards to multi-dimensional manipulation. Is this missing from aeon's API and should I open up a Feature Request + PR? |
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Hi @wayneadams, part of what you are mentioning is currently being worked on PR #1244. The goal of the PR is to create a broadcaster for series estimators (which works on single time series) to be able to use them as collections estimators (which works on multiple time series) in your pipelines. Concerning the selection of subset of channels, you would have to do it yourself, although a channel selection module is currently being worked on (see #1270). While this is being worked on, I fear you would have to do some tinkering and looping yourself, happy to help if needed. |
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Hi @wayneadams, part of what you are mentioning is currently being worked on PR #1244. The goal of the PR is to create a broadcaster for series estimators (which works on single time series) to be able to use them as collections estimators (which works on multiple time series) in your pipelines.
Concerning the selection of subset of channels, you would have to do it yourself, although a channel selection module is currently being worked on (see #1270).
While this is being worked on, I fear you would have to do some tinkering and looping yourself, happy to help if needed.