On 12/07/2015 04:33 AM, Alexandre Gramfort wrote: >> How do you plan to represent variable-length time series? Lists of 1d numpy >> arrays work but would be slow I guess. The ideal representation needs to be >> compatible with grid search and fast. > good point. I was thinking of forcing all time series to have the same length. > or use dtype = object like we do it in \epsilon-kNN to return a > different number of neighbors for each sample. > hello pandora's box ;) I thought we don't want to have time-series specific code?
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