Thanks everyone for your suggested. I will have a look at PipeGraph - which might be a suitable option for us as Guillaume suggested. If it works out, I will share it Thanks David On 02/28/2018 08:29 AM, scikit-learn-request@python.org wrote:

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Today's Topics:

1. New Transformer (David Burns) 2. Re: New Transformer (Guillaume Lema?tre) 3. Re: New Transformer (Manuel Castej?n Limas)

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Message: 1 Date: Tue, 27 Feb 2018 12:02:27 -0500 From: David Burns <david.mo.burns@gmail.com> To: scikit-learn@python.org Subject: [scikit-learn] New Transformer Message-ID: <726f2e70-63eb-783f-b470-5ea45af930e5@gmail.com> Content-Type: text/plain; charset="utf-8"; Format="flowed"

First post on this mailing list.

I have been working with time series data for a project, and thought I could contribute a new transformer to segment time series data using a sliding window, with variable overlap. I have attached demonstration of how this would fit in the existing framework. The only challenge for me here is that the transformer needs to transform both the X and y variable in order to perform the segmentation. I am not sure from the documentation how to implement this in the framework.

Overlapping segments is a great way to boost performance for time series classifiers, so this may be a worthwhile contribution for some in this area of ML. Ultimately, model_selection.TimeSeries.Split would need to be modified to support overlapping segments, or a new class created to enable validation for this.

Please let me know if this would be a worthwhile contribution, and if so how to go about transforming the target vector y in the framework / pipeline?

Thanks!

David Burns