I have a time series of (x,y) values.
When plotted as a scattergram with a line showing the points in sequence it is
possible to see that the data points tend to fall along a rough line (with
possible retracements) for some time before settling into a different line.
This happens multiple times in a data set.
If I visually estimate the start and end date of each set of contiguous points
that form a rough line I can obviously perform a linear regression on those
points but for a large number of points I would like to automatically partition
the sequence into multiple regression lines meeting some sort of maximum error
criterion and perform a regression on each partition.
Is there support for this sort of thing in scikit-learn? I’ve searched for
this info but I’m not very familiar with this area yet and I’m probably
ignorant of the most relevant search terms.
Cheers,
Dieter.
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